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Tytuł:
Passivity-based optimal control of discrete-time nonlinear systems
Autorzy:
Binazadeh, T.
Shafiei, M. H.
Powiązania:
https://bibliotekanauki.pl/articles/205917.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
nonlinear discrete-time systems optimal passivity-based control
genetic optimization algorithm
Opis:
In this paper, a passivity-based optimal controlmethod for a broad class of nonlinear discrete-time systems is proposed. The resulting control law is a static output feedback law which is practically preferred with respect to the state feedback law and is simple to implement. The control law has a general structure with adjustable parameters which are tuned, using an optimization method (genetic algorithm), to minimize an arbitrary cost function. By choosing this cost function it is possible to shape the transient response of the closed-loop system, as it is desirable. An illustrative ex ample shows the effectiveness of the proposed approach.
Źródło:
Control and Cybernetics; 2013, 42, 3; 627-637
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Comparative Study of PID Controller Tuning Using GA, EP, PSO and ACO
Autorzy:
Nagaraj, B.
Vijayakumar, P.
Powiązania:
https://bibliotekanauki.pl/articles/384767.pdf
Data publikacji:
2011
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
ant colony algorithm
evolutionary program
genetic algorithm particle swarm optimization and soft computing
Opis:
Proportional - Integral - Derivative control schemes continue to provide the simplest and effective solutions to most of the control engineering applications today. How ever PID controller are poorly tuned in practice with most of the tuning done manually which is difficult and time consuming. This article comes up with a hybrid approach involving Genetic Algorithm (GA), Evolutionary Pro gramming (EP), Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO). The proposed hybrid algorithm is used to tune the PID parameters and its per formance has been compared with the conventional me thods like Ziegler Nichols and Cohen Coon method. The results obtained reflect that use of heuristic algorithm based controller improves the performance of process in terms of time domain specifications, set point tracking, and regulatory changes and also provides an optimum stability. Speed control of DC motor process is used to assess the efficacy of the heuristic algorithm methodology
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2011, 5, 2; 42-48
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Some Aspects of the Application of Genetic Algorithm for Solving the Assignment Problem of Tasks to Resources in a Transport Company
Autorzy:
Izdebski, Mariusz
Jacyna, Marianna
Powiązania:
https://bibliotekanauki.pl/articles/504281.pdf
Data publikacji:
2014
Wydawca:
Międzynarodowa Wyższa Szkoła Logistyki i Transportu
Tematy:
assignment problem
genetic algorithm
optimization
Opis:
The article defines the assignment problem of tasks to resources in a transport company. The paper describes mathematical model of a transport system taking into account the assignment of vehicles to the tasks. It also provides stages of creation of the genetic algorithm for solving the assignment problem in the transport company.
Źródło:
Logistics and Transport; 2014, 21, 1; 13-20
1734-2015
Pojawia się w:
Logistics and Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of the pulse transformer using circuit-field model
Autorzy:
Łyskawiński, W.
Knypiński, Ł.
Nowak, L.
Jędryczka, C.
Powiązania:
https://bibliotekanauki.pl/articles/1395761.pdf
Data publikacji:
2013
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
pulse transformer
optimization
genetic algorithm
Opis:
The paper presents the new strategy of the optimization of pulse transformer (PT). In order to reduce calculation time the optimization problem has been decomposed into two stages. In the first stage, to determine functional parameters of PT the circuit model is used. The goal of circuit calculations is to limit the space of design variables that meets formulated requirements. The genetic algorithm has been applied for this task. In order to include constraints, the penalty function has been engaged. The transformer dimensions obtained in the first stage of calculations are used as initial values in the second stage of design process. In the second stage the field model of PT is employed. Obtained results prove that presented approach allows for fast optimization of the PT design.
Źródło:
Computer Applications in Electrical Engineering; 2013, 11; 159-167
1508-4248
Pojawia się w:
Computer Applications in Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
On Some Aspects of Genetic and Evolutionary Methods for Optimization Purposes
Autorzy:
Woźniak, M.
Połap, D.
Powiązania:
https://bibliotekanauki.pl/articles/227353.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
computational intelligence
genetic algorithm
heuristic algorithm
optimization
Opis:
In this paper, the idea of applying some hybrid genetic algorithms with gradient local search and evolutionary optimization techniques is formulated. For two different test functions the proposed versions of the algorithms have been examined. Research results are presented and discussed to show potential efficiency in optimization purposes.
Źródło:
International Journal of Electronics and Telecommunications; 2015, 61, 1; 7-16
2300-1933
Pojawia się w:
International Journal of Electronics and Telecommunications
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-variable optimization of an ytterbium-doped fiber laser using genetic algorithm
Autorzy:
Hashemi, S. S.
Ghavami, S. S.
Khorsandi, A
Powiązania:
https://bibliotekanauki.pl/articles/175086.pdf
Data publikacji:
2015
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
fiber laser
optimization
genetic algorithm
Opis:
We introduce the genetic algorithm for the optimization of an Yb3+-doped double-clad fiber laser based on a multi-variable scheme. The output characteristic of the laser is numerically simulated using real practical values. This is performed through solving the associated steady-state rate equation and investigating the effects of input variables such as pump and signal wavelengths and length of the fiber on the laser output. It is found that pumping of the medium around 975 nm is conducted to attain the maximum output power of ~34.8 W, while the stability of the outcoupled power is significantly improved when pumping at 920 nm, confirming good agreement with the reported experimental results. We have also found that by using genetic algorithm base multi-variable optimization, the output power can be significantly increased by about three orders of magnitude and reaches to ~28.5 W with optimum and shorter fiber length of ~57.5 m. Obtained results show that based on the genetic algorithm multi-variable discipline, fiber characteristics can be optimized according to the gaining of maximum output power.
Źródło:
Optica Applicata; 2015, 45, 3; 355-367
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Structural weight minimization of high speed vehicle-passenger catamaran by genetic algorithm
Autorzy:
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/258678.pdf
Data publikacji:
2009
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship structure
optimization
topology optimization
sizing optimization
genetic algorithm
Opis:
Reduction of hull structural weight is the most important aim in the design of many ship types. But the ability of designers to produce optimal designs of ship structures is severely limited by the calculation techniques available for this task. Complete definition of the optimal structural design requires formulation of size-topology-shape-material optimization task unifying optimization problems from four areas and effective solution of the problem. So far a significant progress towards solution of this problem has not been achieved. In other hand in recent years attempts have been made to apply genetic algorithm (GA) optimization techniques to design of ship structures. An objective of the paper was to create a computer code and investigate a possibility of simultaneous optimization of both topology and scantlings of structural elements of large spacial sections of ships using GA. In the paper GA is applied to solve the problem of structural weight minimisation of a high speed vehicle-passenger catamaran with several design variables as dimensions of the plate thickness, longitudinal stiffeners and transverse frames and spacing between longitudinals and transversal members. Results of numerical experiments obtained using the code are presented. They shows that GA can be an efficient optimization tool for simultaneous design of topology and sizing high speed craft structures.
Źródło:
Polish Maritime Research; 2009, 2; 11-23
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of dental implant using genetic algorithm
Optymalizacja wszczepu stomatologicznego z wykorzystaniem algorytmu genetycznego
Autorzy:
Łodygowski, T.
Szajek, K.
Wierszycki, M.
Powiązania:
https://bibliotekanauki.pl/articles/279418.pdf
Data publikacji:
2009
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
design optimization
genetic algorithm
dental implant
Opis:
The subject of the present work is optimization of the modern implant system Osteoplant, which was created and is still developed by Foundation of University of Medical Sciences in Poznań. Clinical observations point to the occurrence of both early and late complications in the case of all two-component implant systems. In many cases, these problems are caused by mechanical fractures of the implants themselves. The obtained results of the previous studies focused on necessary changes of the implant mechanical behavior, which helped to achieve the required long-term strength. However, modifications of the present dental implant system are not obvious. In this paper, an optimization of the Osteoplant dental implant system, with the use of FEA and genetic algorithms is discussed.
Przedmiotem prezentowanej pracy jest problem optymalizacji systemu implantologicznego Osteoplant, który został opracowany i wciąż jest ulepszany przez Fundację Uniwersytetu Medycznego w Poznaniu. Obserwacje kliniczne potwierdzają występowanie powikłań zarówno we wczesnej, jak i późnej fazie użytkowania implantu. Dotychczas otrzymane wyniki wskazują, że wydłużenie bezawaryjnego okresu użytkowania implantu wymaga wprowadzenia zmian w jego pracy mechanicznej. Jednakże, ustalenie szczegłów modyfikacji nie jest oczywiste. W artykule została opisana procedura optymalizacji systemu implantologicznego Osteoplant z użyciem analizy metodą elementów skończonych oraz algorytmu genetycznego.
Źródło:
Journal of Theoretical and Applied Mechanics; 2009, 47, 3; 573-598
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Efficiency improvement of switched reluctance generator using optimization techniques
Autorzy:
Reis, M. R. C.
Araújo, W. R. H.
Calixto, W. P.
Powiązania:
https://bibliotekanauki.pl/articles/136169.pdf
Data publikacji:
2017
Wydawca:
EEEIC International Barbara Leonowicz Szabłowska
Tematy:
switched reluctance generator
optimization
control
genetic algorithm
Opis:
This article introduces the switched reluctance machine operating as a generator. This kind of electrical machine delivers CC power at the output and the energy generated can be controlled through several variables. In this work, the switching angles of the machine's power converter are optimized using deterministic and heuristic techniques so that the output power is kept constant via PI controller while guaranteeing maximum value for machine performance, even for different excitation values and mechanical power on the shaft.
Źródło:
Transactions on Environment and Electrical Engineering; 2017, 2, 1; 74-80
2450-5730
Pojawia się w:
Transactions on Environment and Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Ship Trajectory Control Optimization in Anti-collision Maneuvering
Autorzy:
Zhang, J. F.
Yang, X. D.
Zhang, D.
Haugen, S.
Powiązania:
https://bibliotekanauki.pl/articles/116373.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
anticollision
ship trajectory
genetic algorithm
route optimization
Opis:
A lot of attention is being paid to ship’s intelligent anti‐collision by researchers. Several solutions have been introduced to find an optimum trajectory for ship, such as Game Theory, Genetic or Evolutionary Algorithms and so on. However, ship’s maneuverability should be taken into consideration before their real applications. Ship’s trajectory control in anti‐collision maneuvering is studied in this paper. At first, a simple linear ship maneuverability model is introduced to simulate its movement under different speed and rudder angle. After that, ship’s trajectory control is studied by considering the duration of rudder, operation distance to turning points, and maximum angular velocity. The details for algorithm design are also introduced. By giving some restrictions according to the requirements from COLREGs, the intervals for rudder angle in different circumstances can be determined based on the curves. The results can give very meaningful guidance for seafarers when making decisions.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2013, 7, 1; 89-93
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Passive loop coordinates optimization for mitigation of magnetic field value in the proximity of a power line
Autorzy:
Książkiewicz, M.
Powiązania:
https://bibliotekanauki.pl/articles/97704.pdf
Data publikacji:
2015
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
power line
magnetic field
optimization
genetic algorithm
Opis:
The paper relates to the distribution of the magnetic field generated by the overhead power line, and it’s reduction in the area of interest using a conductive loop placed in the space near the line. The paper presents results obtained from an original program written in C ++, which implements the procedure for calculating the magnetic field generated by overhead line and a genetic algorithm used to optimize the location and loop compensation factor. Examples of the program are presented for horizontal single-track line and three different shielding loop configurations. The first relates to a single loop (4 to 5 parameters to optimize - 4 position coordinates (y, z) and the compensation factor), the second case involves two loops with one common conductor (6 to 8 parameters - 6 coordinates (y, z) and 0 to 2 compensation factors), the third case concerns two independent loops (8 to 10 parameters - 8 coordinates (y, z) and 0 to 2 of the compensation factors). In addition similar calculations are performed for single-track line with two earth wires.
Źródło:
Computer Applications in Electrical Engineering; 2015, 13; 77-87
1508-4248
Pojawia się w:
Computer Applications in Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimizing the number of docks at transhipment terminals using genetic algorithm
Autorzy:
Izdebski, M.
Jacyna-Gołda, I.
Powiązania:
https://bibliotekanauki.pl/articles/242009.pdf
Data publikacji:
2017
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
transhipment terminal
genetic algorithm
optimization
cross docking
Opis:
This article presents the issue of designating the number of docks at the transhipment terminals using genetic algorithm. Transhipment terminals refer to cross-docking terminals. The main factor that influences on the number of these docks is the stream of cargo flowing into the given terminal. In order to determine this flow of cargo the mathematical model of the distribution of this flow was developed. This model takes into account constraints like those that e.g. processing capacity at the transhipment terminal cannot be exceeded or demand of recipients must be met. The criterion function in this model determines the minimum cost of the flow of cargo between all objects in the transport network. To designate the optimal stream of cargo flowing into the transport network the genetic algorithm was developed. In this article, the stages of construction of this algorithm were presented. The structure processed by the algorithm, the process of crossover and mutation were described. In the article in order to solve the problem of designating the number of docks at the transhipment terminals the genetic algorithm was developed.
Źródło:
Journal of KONES; 2017, 24, 4; 369-376
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Assessment of High-Order-Mode Analysis and Shape Optimization of Expansion Chamber Mufflers
Autorzy:
Chiu, M. C.
Chang, Y. C.
Powiązania:
https://bibliotekanauki.pl/articles/178079.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
higher order wave
eigenfunction
optimization
genetic algorithm
Opis:
A substantial quantity of research on muffler design has been restricted to a low frequency range using the plane wave theory. Based on this theory, which is a one-dimensional wave, no higher order wave has been considered. This has resulted in underestimating acoustical performances at higher frequencies when doing muffler analysis via the plane wave model. To overcome the above drawbacks, researchers have assessed a three-dimensional wave propagating for a simple expansion chamber muffler. Therefore, the acoustic effect of a higher order wave (a high frequency wave) is considered here. Unfortunately, there has been scant research on expansion chamber mufflers equipped with baffle plates that enhance noise elimination using a higher-order-mode analysis. Also, space-constrained conditions of industrial muffler designs have never been properly addressed. So, in order to improve the acoustical performance of an expansion chamber muffler within a constrained space, the optimization of an expansion chamber muffler hybridized with multiple baffle plates will be assessed. In this paper, the acoustical model of the expansion chamber muffler will be established by assuming that it is a rigid rectangular tube driven by a piston along the tube wall. Using an eigenfunction (higher- order-mode analysis), a four-pole system matrix for evaluating acoustic performance (STL) is derived. To improve the acoustic performance of the expansion chamber muffler, three kinds of expansion chamber mufflers (KA-KC) with different acoustic mechanisms are introduced and optimized for a targeted tone using a genetic algorithm (GA). Before the optimization process is performed, the higher-order-mode mathematical models of three expansion chamber mufflers (A-C) with various allocations of inlets/outlets and various chambers are also confirmed for accuracy. Results reveal that the STL of the expansion chamber mufflers at the targeted tone has been largely improved and the acoustic performance of a reverse expansion chamber muffler is more efficient than that of a straight expansion chamber muffler. Moreover, the STL of the expansion chamber mufflers will increase as the number of the chambers that separate with baffles increases.
Źródło:
Archives of Acoustics; 2014, 39, 4; 489-499
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance investigation and element optimization of 2D array transducer using Bat Algorithm
Autorzy:
Tantawy, Dina Mohamed
Eladawy, Mohamed
Hassan, Mohamed Alimaher
Mubarak, Roaa
Powiązania:
https://bibliotekanauki.pl/articles/140685.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
2D ultrasound arrays
Binary Bat Algorithm
Genetic Algorithm
Optimization
Opis:
One of the least expensive and safest diagnostic modalities routinely used is ultrasound imaging. An attractive development in this field is a two-dimensional (2D) matrix probe with three-dimensional (3D) imaging. The main problems to implement this probe come from a large number of elements they need to use. When the number of elements is reduced the side lobes arising from the transducer change along with the grating lobes that are linked to the periodic disposition of the elements. The grating lobes are reduced by placing the elements without any consideration of the grid. In this study, the Binary Bat Algorithm (BBA) is used to optimize the number of active elements in order to lower the side lobe level. The results are compared to other optimization methods to validate the proposed algorithm.
Źródło:
Archives of Electrical Engineering; 2020, 69, 3; 561-579
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Planning and management of aircraft maintenance using a genetic algorithm
Autorzy:
Kowalski, Mirosław
Izdebski, Mariusz
Żak, Jolanta
Gołda, Paweł
Manerowski, Jerzy
Powiązania:
https://bibliotekanauki.pl/articles/1841824.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
aircraft operation
maintenance
multi-criteria optimization
genetic algorithm
Opis:
The aim of the article was to develop a tool to support the process of planning and managing aircraft (ac) maintenance. Aircraft maintenance management has been presented for scheduled technical inspections resulting from manufacturers’ technical documentation for ac. The authors defined the problem under investigation in the form of a four-phase decisionmaking process taking into account assignment of aircraft to airports and maintenance stations, assignment of crew to maintenance points, setting the schedules, i.e. working days on which aircraft are directed to maintenance facilities. This approach to the planning and management of aircraft maintenance is a new approach, unprecedented in the literature. The authors have developed a mathematical model for aircraft maintenance planning and management in a multi-criteria approach and an optimisation tool based on the operation of a genetic algorithm. To solve the problem, a genetic algorithm was proposed. The individual steps of the algorithm construction were discussed and its effectiveness was verified using real data.
Źródło:
Eksploatacja i Niezawodność; 2021, 23, 1; 143-153
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Recognizing Sets in Evolutionary Multiobjective Optimization
Autorzy:
Gajda-Zagórska, E.
Powiązania:
https://bibliotekanauki.pl/articles/308467.pdf
Data publikacji:
2012
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
basin of attraction
clustering
genetic algorithm
multiobjective optimization
Opis:
Among Evolutionary Multiobjective Optimization Algorithms (EMOA) there are many which find only Paretooptimal solutions. These may not be enough in case of multimodal problems and non-connected Pareto fronts, where more information about the shape of the landscape is required. We propose a Multiobjective Clustered Evolutionary Strategy (MCES) which combines a hierarchic genetic algorithm consisting of multiple populations with EMOA rank selection. In the next stage, the genetic sample is clustered to recognize regions with high density of individuals. These regions are occupied by solutions from the neighborhood of the Pareto set. We discuss genetic algorithms with heuristic and the concept of well-tuning which allows for theoretical verification of the presented strategy. Numerical results begin with one example of clustering in a single-objective benchmark problem. Afterwards, we give an illustration of the EMOA rank selection in a simple two-criteria minimization problem and provide results of the simulation of MCES for multimodal, multi-connected example. The strategy copes with multimodal problems without losing local solutions and gives better insight into the shape of the evolutionary landscape. What is more, the stability of solutions in MCES may be analyzed analytically.
Źródło:
Journal of Telecommunications and Information Technology; 2012, 1; 74-82
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use of computer assistance in order to designate the tasks in the municipal services companies
Autorzy:
Izdebski, M.
Jacyna, M.
Powiązania:
https://bibliotekanauki.pl/articles/241863.pdf
Data publikacji:
2014
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
municipal services companies
transport
optimization
genetic algorithm
verification
Opis:
In this article, the method of designating the tasks in the municipal services companies was described. Presented method consists of three phase: the preparatory phase, the optimization phase and the generated tasks phase. Each phase was characterized. In this paper, the mathematical model of this problem was presented. The function of criterion and the condition on designating the tasks were defined. The minimum route described in the optimization phase was designated by the genetic algorithm. In this paper, the stages of constructing of the genetic algorithm were presented. A structure of the data processed by the algorithm, a function of adaptation, a selection of chromosomes, a crossover, a mutation and an inversion were characterized. A structure of the data was presented as string of natural numbers. In selection process, the roulette method was used and in the crossover, process the operator PMX was presented. The method was verified in programming language C #. The process of verification was divided into two stages. In the first stage, the best parameters of the genetics algorithm were designated. In the second stage, the algorithm was started with these parameters and the result was compared with the random search algorithm. The random search algorithm generates 2000 routes and the best result is compared with the genetic algorithm. The influence of the inversion, the mutation and the crossover on quality of the results was examined.
Źródło:
Journal of KONES; 2014, 21, 2; 105-112
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Planning and management of aircraft maintenance using a genetic algorithm
Autorzy:
Kowalski, Mirosław
Izdebski, Mariusz
Żak, Jolanta
Gołda, Paweł
Manerowski, Jerzy
Powiązania:
https://bibliotekanauki.pl/articles/1841765.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
aircraft operation
maintenance
multi-criteria optimization
genetic algorithm
Opis:
The aim of the article was to develop a tool to support the process of planning and managing aircraft (ac) maintenance. Aircraft maintenance management has been presented for scheduled technical inspections resulting from manufacturers’ technical documentation for ac. The authors defined the problem under investigation in the form of a four-phase decisionmaking process taking into account assignment of aircraft to airports and maintenance stations, assignment of crew to maintenance points, setting the schedules, i.e. working days on which aircraft are directed to maintenance facilities. This approach to the planning and management of aircraft maintenance is a new approach, unprecedented in the literature. The authors have developed a mathematical model for aircraft maintenance planning and management in a multi-criteria approach and an optimisation tool based on the operation of a genetic algorithm. To solve the problem, a genetic algorithm was proposed. The individual steps of the algorithm construction were discussed and its effectiveness was verified using real data.
Źródło:
Eksploatacja i Niezawodność; 2021, 23, 1; 143-153
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part II. Computational simulations
Autorzy:
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/260598.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
Opis:
Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems of the four areas and giving an effective solution of the problem. So far, a significant progress towards the solution of the problem has not been obtained. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area on a high speed vehicle-passenger catamaran structure, with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members, taken into account. Details of the computational models were at the level typical for conceptual design. Scantlings were analyzed by using selected rules of a classification society. The results of numerical experiments with the use of the developed algorithm, are presented. They show that the proposed genetic algorithm can be an efficient tool for multi-objective optimization of ship structures. The paper is published in three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational investigations, and Part III: Analysis of the results.
Źródło:
Polish Maritime Research; 2011, 3; 3-30
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Function optimization using metaheuristics
Autorzy:
Pilski, M.
Seredyński, F.
Powiązania:
https://bibliotekanauki.pl/articles/92887.pdf
Data publikacji:
2006
Wydawca:
Uniwersytet Przyrodniczo-Humanistyczny w Siedlcach
Tematy:
particle swarm optimization (PSO)
artificial immune system
genetic algorithm
function optimization
Opis:
The paper presents the results of comparison of three metaheuristics that currently exist in the problem of function optimization. The first algorithm is Particle Swarm Optimization (PSO) - the algorithm has recently emerged. The next one is based on a paradigm of Artificial Immune System (AIS). Both algorithms are compared with Genetic Algorithm (GA). The algorithms are applied to optimize a set of functions well known in the area of evolutionary computation. Experimental results show that it is difficult to unambiguously select one best algorithm which outperforms other tested metaheuristics.
Źródło:
Studia Informatica : systems and information technology; 2006, 1(7); 77-91
1731-2264
Pojawia się w:
Studia Informatica : systems and information technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Analog Circuit Based on Computational Intelligence Techniques
Autorzy:
Oltean, G.
Hintea, S.
Şipos, E.
Powiązania:
https://bibliotekanauki.pl/articles/385049.pdf
Data publikacji:
2009
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
analog circuit design
optimization
genetic algorithm
neuro-fuzzy systems
Opis:
This paper presents a new method for analog circuit design optimization. Our approach turns to good account the advantages offered by computational intelligence techniques. Design objectives can be expressed in a flexible manner using fuzzy sets. This way appears the possibility to consider different degrees for requirement achievements and acceptability degree for a particular solution. Neuro-fuzzy systems (universal approximators) are used to model the complex multi-variable and nonlinear circuit performances. These models satisfy two main requirements: high accuracy and low computation complexity. An efficient and robust genetic algorithm does avoiding local minima the exploration of the large, multidimensional solution space in quest for the optimal solution.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2009, 3, 2; 63-69
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The application of genetic algorithm in the assignment problems in the transportation company
Autorzy:
Izdebski, M.
Jacyna, M.
Powiązania:
https://bibliotekanauki.pl/articles/247149.pdf
Data publikacji:
2018
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
assignment problem
genetic algorithm
multi-criterion optimization
transportation company
Opis:
The article presents the problem of the task assignment of the vehicles for the transportation company, which deals with the transport of the cargo in the full truckload system. The presented problem is a complex decision making issue which has not been analysed in the literature before. There must be passed through two stages in order to solve the task assignment problem of the vehicles for the transportation company. The first stage is to designate the tasks, the other one is to determine the number of the vehicles that perform these tasks. The task in the analysed problem is defined as transporting the cargo from the suppliers to the recipients. The transportation routes of the cargo must be determined. In order to solve the task assignment problem of the vehicles, the genetic algorithm has been developed. The construction stages of this algorithm are presented. The algorithm has been developed to solve the multi-criteria decision problem. What is more, the algorithm is verified by the use of the real input data.
Źródło:
Journal of KONES; 2018, 25, 4; 133-140
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Two stage optimization of the PMSM with excitation system composed of different materials
Autorzy:
Knypiński, Ł.
Nowak, L.
Powiązania:
https://bibliotekanauki.pl/articles/97722.pdf
Data publikacji:
2013
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
electric machines
permanent magnet synchronous motor
optimization
genetic algorithm
Opis:
The paper presents the algorithm and software for the optimization of the rotor structure of the permanent magnet synchronous motor with magnet composed of two materials about different magnetic properties. The software consists of two modules: a numerical model of the PMSM motor and an optimization solver. Numerical implementation is based on finite element method. The optimization module has been elaborated employing the Delphi environment. For the rotor structure optimization the genetic algorithm has been applied Selected results of the calculation are presented and discussed.
Źródło:
Computer Applications in Electrical Engineering; 2013, 11; 148-158
1508-4248
Pojawia się w:
Computer Applications in Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of electric and magnetic field intensities in proximity of power lines using genetic and particle swarm algorithms
Autorzy:
Król, K.
Machczyński, W.
Powiązania:
https://bibliotekanauki.pl/articles/141588.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
power line
electric field
magnetic field
optimization
genetic algorithm
particle swarm algorithm
Opis:
The paper presents optimization of power line geometrical parameters aimed to reduce the intensity of the electric field and magnetic field intensity under an overhead power line with the use of a genetic algorithm (AG) and particle swarm optimization (PSO). The variation of charge distribution along the conductors as well as the sag of the overhead line and induced currents in earth wires were taken into account. The conductor sag was approximated by a chain curve. The charge simulation method (CSM) and the method of images were used in the simulations of an electric field, while a magnetic field were calculated using the Biot–Savart law. Sample calculations in a three-dimensional system were made for a 220 kV single – circuit power line. A comparison of the used optimization algorithms was made.
Źródło:
Archives of Electrical Engineering; 2018, 67, 4; 829-843
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective design optimization of five-phase fractional-slot concentrated-winding surface-mounted permanent-magnet machine
Autorzy:
Nekoubin, Amir
Soltani, Jafar
Dowlatshah, Milad
Powiązania:
https://bibliotekanauki.pl/articles/949883.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
Finite Element Method
genetic algorithm
optimization
permanent-magnet motors
Opis:
The multi-phase permanent-magnet machines with a fractional-slot concentratedwinding (FSCW) are a suitable choice for certain purposes like aircraft, marine, and electric vehicles, because of the fault tolerance and high power density capability. The paper aims to design, optimize and prototype a five-phase fractional-slot concentrated-winding surface-mounted permanent-magnet motor. To optimize the designed multi-phase motor a multi-objective optimization technique based on the genetic algorithm method is applied. The machine design objectives are to maximize torque density of the motor and maximize efficiency then to determine the best choice of the designed machine parameters. Then, the two-dimensional Finite Element Method (2D-FEM) is employed to verify the performance of the optimized machine. Finally, the optimized machine is prototyped. The paper found that the results of the prototyped machine validate the results of theatrical analyses of the machine and accurate consideration of the parameters improved the acting of the machine.
Źródło:
Archives of Electrical Engineering; 2020, 69, 4; 873-889
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid ant colony for multiresponse mixed-integer problems
Autorzy:
Kushwaha, S.
Mukherjee, I.
Powiązania:
https://bibliotekanauki.pl/articles/409419.pdf
Data publikacji:
2012
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
ant colony optimization(ACO)
desirability functions
genetic algorithm (GA)
multiple response optimization(MRO)
Opis:
In this paper, a hybrid ant colony optimization (ACO) is used to solve a multiple response optimization problem with mixed-integer (MI) search space. The work reported in this paper may be clasified into three part. The first part discusses on relevant litratures and the methodology to solve multiple response optimization problem. The second part provide details on the working principal, parameter tuning of a hybrid ACO proposed for mixed integer state space. In the hybrid ACO, genetic algorithm (GA) is used for intensification of the search strategy. Standard single response (objective) test functions are selected to verify the suitability of hybrid ACO. The third part of this research work illustrates the application of the hybrid ACO in a multiple response optimization (MRO) problem. Statistical experimentation, partial least square regression, 'maximin' desirability function, and hybrid ACO is used to solve the MRO problem. The results confirm the suitability of the hybid ACO for a typical MI MRO problem.
Źródło:
Research in Logistics & Production; 2012, 2, 4; 317-327
2083-4942
2083-4950
Pojawia się w:
Research in Logistics & Production
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Use of a Global Index of Acoustic Assessment for Predicting Noise in Industrial Rooms and Optimizing the Location of Machinery and Workstations
Autorzy:
Pleban, D.
Powiązania:
https://bibliotekanauki.pl/articles/89745.pdf
Data publikacji:
2014
Wydawca:
Centralny Instytut Ochrony Pracy
Tematy:
noise
machinery
optimization
genetic algorithm
hałas
maszyny
optymalizacja
algorytm genetyczny
Opis:
This paper describes the results of a study aimed at developing a tool for optimizing the location of machinery and workstations. A global index of acoustic assessment of machines was developed for this purpose. This index and a genetic algorithm were used in a computer tool for predicting noise emission of machines as well as optimizing the location of machines and workstations in industrial rooms. The results of laboratory and simulation tests demonstrate that the developed global index and the genetic algorithm support measures aimed at noise reduction at workstations.
Źródło:
International Journal of Occupational Safety and Ergonomics; 2014, 20, 4; 627-638
1080-3548
Pojawia się w:
International Journal of Occupational Safety and Ergonomics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Simultaneous optimization of flotation column performance using genetic evolutionary algorithm
Autorzy:
Nakhaei, F.
Irannajad, M.
Yousefikhoshbakht, M.
Powiązania:
https://bibliotekanauki.pl/articles/110806.pdf
Data publikacji:
2016
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
flotation column
optimization
genetic algorithm
non-linear regression
upgrading curve
Opis:
Column flotation is a multivariable process. Its optimization guarantees the metallurgical yield of the process, expressed by the grade and recovery of the concentrate. The present work aimed at applying genetic algorithms (GAs) to optimize a pilot column flotation process which is characterized by being difficult to be optimized via conventional methods. A non-linear mathematical model was used to describe the dynamic behavior of the multivariable process. The solution of the optimization problem using conventional algorithms does not always lead to convergence because of the high dimensionality and non-linearity of the model. In order to deal with this process, the use of a genetic evolutionary algorithm is justified. In this way, GA was coupled with the multivariate non-linear regression (MNLR) of the column flotation metallurgical performance as a fitting function in order to optimize the column flotation process. Then, this kind of intelligent approach was verified by using mineral processing approaches such as Halbich’s upgrading curve. The aim of the optimization through GAs was searching for the process inputs that maximize the productivity of copper in the Sarcheshmeh pilot plant. In this case, the simulation optimization problem was defined as finding the best values for the froth height, chemical reagent dosage, wash water, air flow rate, air holdup, and Cu grade in rougher and column feed streams. The results indicated that GA was a robust and powerful search method to find the best values of the flotation column model parameters that lead to more reliable simulation predictions at a reasonable time. Based on the grade–recovery Halbich upgrading curve, the MNLR model coupled with GA can be used for determination of the flotation optimum conditions.
Źródło:
Physicochemical Problems of Mineral Processing; 2016, 52, 2; 874-893
1643-1049
2084-4735
Pojawia się w:
Physicochemical Problems of Mineral Processing
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Numerical analysis of tailing dam with calibration based on genetic algorithm and geotechnical monitoring data
Autorzy:
Grosel, Szczepan
Powiązania:
https://bibliotekanauki.pl/articles/1845160.pdf
Data publikacji:
2021
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
soil parameters
optimization
slope stability
genetic algorithm
observational method
monitoring
Opis:
The article presents a method of calibration of material parameters of a numerical model based on a genetic algorithm, which allows to match the calculation results with measurements from the geotechnical monitoring network. This method can be used for the maintenance of objects managed by the observation method, which requires continuous monitoring and design alterations. The correctness of the calibration method has been verified on the basis of artificially generated data in order to eliminate inaccuracies related to approximations resulting from the numerical model generation. Using the example of the tailing dam model the quality of prediction of the selected measurement points was verified. Moreover, changes of factor of safety values, which is an important indicator for designing this type of construction, were analyzed. It was decided to exploit the case of dam of reservoir, which is under continuous construction, that is dam height is increasing constantly, because in this situation the use of the observation method is relevant.
Źródło:
Studia Geotechnica et Mechanica; 2021, 43, 1; 34-47
0137-6365
2083-831X
Pojawia się w:
Studia Geotechnica et Mechanica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Quality improvement of a gear transmission by means of genetic algorithm
Autorzy:
Lempa, Paweł
Lisowski, Edward
Masui, Fumito
Filo, Grzegorz
Ptaszynski, Michal
Domagała, Mariusz
Fabiś-Domagała, Joanna
Powiązania:
https://bibliotekanauki.pl/articles/104043.pdf
Data publikacji:
2019
Wydawca:
Stowarzyszenie Menedżerów Jakości i Produkcji
Tematy:
optimization
genetic algorithm
gear transmission
optymalizacja
algorytm genetyczny
przekładnia zębata
Opis:
The article deals with the issue of quality improvement of a gear transmission by optimizing its geometry with the use of genetic algorithms. The optimization method is focused on increasing productivity and efficiency of the pump and reducing its pulsation. The best results are tested on mathematical model and automatically modelled in 3D be means of PTC Creo Software. The developed solution proved to be an effective tool in the search for better results, which greatly improved parameters of pump especially reduced flow pulsation.
Źródło:
Quality Production Improvement - QPI; 2019, 1, 1; 386-393
2657-8603
Pojawia się w:
Quality Production Improvement - QPI
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimal design of sandwich panels with a soft core
Optymalne projektowanie płyt warstwowych z miękkim rdzeniem
Autorzy:
Studziński, R.
Pozorski, Z.
Garstecki, A.
Powiązania:
https://bibliotekanauki.pl/articles/279446.pdf
Data publikacji:
2009
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
sandwich panels
soft-core
Pareto optimization
soft computing
genetic algorithm
Opis:
The main issue taken up in the paper is to find optimal designs of multispan sandwich panels with slightly profiled steel facings and polyurethane foam core (PUR), which would satisfy conflicting demands of the market, i.e. minimal variance in types of panels, maximum range of application and minimum cost. The aim is to find dimensional and material parameters of panels which generate minimum cost and maximum length of span under prescribed loads in ultimate and serviceability limit states. The multi-criterion optimization problem is formulated in such a way, where the length of the span plays two roles, namely a design variable and a component of a vector objective function. An evolutionary algorithm is used. Numerous inequality constraints are introduced in two ways: directly and by external penalty functions.
Wpracy podejmuje się problem optymalizacji wieloprzęsłowych płyt warstwowych z rdzeniem z poliuretanu (PUR) i okładzinami stalowymi lekko profilowanymi. Poszukuje się rozwiązań, które spełnią sprzeczne wymagania rynku, mianowicie: minimalizację typoszeregu płyt, maksymalizację zakresu ich zastosowania oraz minimalizację kosztu produkcji. Celem optymalizacji jest znalezienie parametrów geometrycznych i materiałowych płyt warstwowych, które minimalizują koszt oraz maksymalizują dopuszczalną rozpiętość dla ustalonych obciążeń i przy spełnieniu stanów granicznych nośności i użytkowalności. W wielokryterialnym sformułowaniu problemu optymalizacyjnego rozpiętość pełni dwie funkcje. Jest ona równocześnie zmienną projektową i składową wektora funkcji celu. Jako narzędzie optymalizacji wykorzystano algorytmy genetyczne. Ograniczenia nierównościowe wprowadzono do procedury optymalizacyjnej za pomocą zewnętrznej funkcji kary oraz jawnie.
Źródło:
Journal of Theoretical and Applied Mechanics; 2009, 47, 3; 685-699
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Use of Heuristic Algorithms to Optimize the Transport Issues on the Example of Municipal Services Companies
Autorzy:
Izdebski, M.
Powiązania:
https://bibliotekanauki.pl/articles/223579.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
municipal services companies
transport
optimization
genetic algorithm
ant algorithm
usługi komunalne
optymalizacja
algorytm genetyczny
Opis:
In this article the main optimization problems in the municipal services companies were presented. These problems concern the issue of vehicle routing. The mathematical models of these problems were described. The function of criterion and the conditions on designating the vehicle routing were defined. In this paper the hybrid algorithm solving the presented problems was proposed. The hybrid algorithm consists of two heuristic algorithms: the ant and the genetic algorithm. In this paper the stages of constructing of the hybrid algorithm were presented. A structure of the data processed by the algorithm, a function of adaptation, a selection of chromosomes, a crossover, a mutation and an inversion were characterized. A structure of the data was presented as string of natural numbers. In selection process the roulette method was used and in the crossover process the operator PMX was presented. This algorithm was verified in programming language C #. The process of verification was divided into two stages. In the first stage the best parameters of the hybrid algorithm were designated. In the second stage the algorithm was started with these parameters and the result was compared with the random search algorithm. The random search algorithm generates 2000 routes and the best result is compared with the hybrid algorithm.
Źródło:
Archives of Transport; 2014, 29, 1; 27-36
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A genetic algorithm and B&B algorithm for integrated production scheduling, preventiveand corrective maintenance to save energy
Autorzy:
Sadiqi, Assia
El Abbassi, Ikram
El Barkany, Abdellah
Darcherif, Moumen
El Biyaali, Ahmed
Powiązania:
https://bibliotekanauki.pl/articles/1841396.pdf
Data publikacji:
2020
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
scheduling
maintenance
genetic algorithm
branch
bound
MILP
modeling
optimization
CPLEX
Python
Opis:
The rapid global economic development of the world economy depends on the availability of substantial energy and resources, which is why in recent years a large share of non-renewable energy resources has attracted interest in energy control. In addition, inappropriate use of energy resources raises the serious problem of inadequate emissions of greenhouse effect gases, with major impact on the environment and climate. On the other hand, it is important to ensure efficient energy consumption in order to stimulate economic development and preserve the environment. As scheduling conflicts in the different workshops are closely associated with energy consumption. However, we find in the literature only a brief work strictly focused on two directions of research: the scheduling with PM and the scheduling with energy. Moreover, our objective is to combine both aspects and directions of in-depth research in a single machine. In this context, this article addresses the problem of integrated scheduling of production, preventive maintenance (PM) and corrective maintenance (CM) jobs in a single machine. The objective of this article is to minimize total energy consumption under the constraints of system robustness and stability. A common model for the integration of preventive maintenance (PM) in production scheduling is proposed, where the sequence of production tasks, as well as the preventive maintenance (PM) periods and the expected times for completion of the tasks are established simultaneously; this makes the theory put into practice more efficient. On the basis of the exact Branch and Bound method integrated on the CPLEX solver and the genetic algorithm (GA) solved in the Python software, the performance of the proposed integer binary mixed programming model is tested and evaluated. Indeed, after numerically experimenting with various parameters of the problem, the B&B algorithm works relatively satisfactorily and provides accurate results compared to the GA algorithm. A comparative study of the results proved that the model developed was sufficiently efficient.
Źródło:
Management and Production Engineering Review; 2020, 11, 4; 138-148
2080-8208
2082-1344
Pojawia się w:
Management and Production Engineering Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new auto adaptive fuzzy hybrid particle swarm optimization and genetic algorithm
Autorzy:
Dziwiński, Piotr
Bartczuk, Łukasz
Paszkowski, Józef
Powiązania:
https://bibliotekanauki.pl/articles/1837533.pdf
Data publikacji:
2020
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
hybrid methods
Particle Swarm Optimization
Genetic Algorithm
fuzzy systems
multimodal function
Opis:
The social learning mechanism used in the Particle Swarm Optimization algorithm allows this method to converge quickly. However, it can lead to catching the swarm in the local optimum. The solution to this issue may be the use of genetic operators whose random nature allows them to leave this point. The degree of use of these operators can be controlled using a neuro-fuzzy system. Previous studies have shown that the form of fuzzy rules should be adapted to the fitness landscape of the problem. This may suggest that in the case of complex optimization problems, the use of different systems at different stages of the algorithm will allow to achieve better results. In this paper, we introduce an auto adaptation mechanism that allows to change the form of fuzzy rules when solving the optimization problem. The proposed mechanism has been tested on benchmark functions widely adapted in the literature. The results verify the effectiveness and efficiency of this solution.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 2; 95-111
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
GPU-based tuning of quantum-inspired genetic algorithm for a combinatorial optimization problem
Autorzy:
Nowotniak, R.
Kucharski, J.
Powiązania:
https://bibliotekanauki.pl/articles/201268.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
quantum-inspired genetic algorithm
evolutionary computing
meta-optimization
parallel algorithms
GPGPU
Opis:
This paper concerns efficient parameters tuning (meta-optimization) of a state-of-the-art metaheuristic, Quantum-Inspired Genetic Algorithm (QIGA), in a GPU-based massively parallel computing environment (NVidia CUDATMtechnology). A novel approach to parallel implementation of the algorithm has been presented. In a block of threads, each thread transforms a separate quantum individual or different quantum gene; In each block, a separate experiment with different population is conducted. The computations have been distributed to eight GPU devices, and over 400× speedup has been gained in comparison to Intel Core i7 2.93GHz CPU. This approach allows efficient meta-optimization of the algorithm parameters. Two criteria for the meta-optimization of the rotation angles in quantum genes state space have been considered. Performance comparison has been performed on combinatorial optimization (knapsack problem), and it has been presented that the tuned algorithm is superior to Simple Genetic Algorithm and to original QIGA algorithm.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 2; 323-330
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance Comparison of Optimization Methods for Flat-Top Sector Beamforming in a Cellular Network
Autorzy:
Nandi, Pampa
Roy, Jibendu Sekhar
Powiązania:
https://bibliotekanauki.pl/articles/2142316.pdf
Data publikacji:
2022
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
flat-top sector beam
particle swarm optimization
real-coded genetic algorithm
Opis:
The flat-top radiation pattern is necessary to form an appropriate beam in a sectored cellular network and to pro vide users with best quality services. The flat-top pattern offers sufficient power and allows to minimize spillover of signal to adjacent sectors. The flat-top sector beam pattern is relied upon In sectored cellular networks, in multiple-input multiple-output (MIMO) systems and ensures a nearly constant gain in the desired cellular sector. This paper presents a comparison of such optimization techniques as real-coded genetic algorithm (RGA) and particle swarm optimization (PSO), used in cellular networks in order to achieve optimum flat-top sector patterns. The individual parameters of flat-top sector beams, such as cellular coverage, ripples in the flat-top beam, spillover of radiation to the adjacent sectors and side lobe level (SLL) are investigated through optimization performed for 40◦ and 60◦ sectors. These parameters are used to compare the performance of the optimized RGA and PSO algorithms. Overall, PSO outperforms the RGA algorithm.
Źródło:
Journal of Telecommunications and Information Technology; 2022, 3; 39--46
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of the impact multi-mass vibration absorbers
Autorzy:
Kernytskyy, I.
Diveyev, B.
Horbaj, O.
Hlobchak, M.
Kopytko, M.
Zachek, O.
Powiązania:
https://bibliotekanauki.pl/articles/886928.pdf
Data publikacji:
2017
Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Wydawnictwo Szkoły Głównej Gospodarstwa Wiejskiego w Warszawie
Tematy:
impact damping system
multi-mass
dynamic vibration absorber
optimization
simultaneous optimization
genetic algorithm
Boltzmann approximation
Opis:
Optimization of the impact multi-mass vibration absorbers. The problem of attaching dynamic vibration absorber (DVA) to a discrete multi-degree-of-freedom or continuous structure has been outlined in many papers and monographs. An impact damping system can overcome some limitations by impact as the damping medium and impact mass interaction as the damping mechanism. The paper contemplates the provision of DVA with the several of the impact masses. Such originally designed absorbers reduce vibration selectively in maximum vibration mode without introducing vibration in other modes. An impact damper is a passive control device which takes the form of a freely moving mass, constrained by stops attached to the structure under control, i.e. the primary structure. The damping results from the exchange of momentum during impacts between the mass and the stops as the structure vibrates. The paper contemplates the provision of the impact multi-mass DVA’s with masses collisions for additional damping. For some cases of DVA optimization such a design seems more effective than conventional multi-mass DVA with independent mass moving. A technique is developed to give the optimal DVA’s for the elimination of excessive vibration in harmonic stochastic and impact loaded systems.
Źródło:
Scientific Review Engineering and Environmental Sciences; 2017, 26, 3[77]
1732-9353
Pojawia się w:
Scientific Review Engineering and Environmental Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Stacking sequence optimization of composite beams with different layer thicknesses
Autorzy:
Karaçam, F
Timarci, T
Powiązania:
https://bibliotekanauki.pl/articles/102025.pdf
Data publikacji:
2015
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
laminated composite beams
static analysis
genetic algorithm
layer thickness
stacking sequence optimization
Opis:
In this study, stacking sequence optimization of composite beams with different layer thicknesses is investigated for various boundary conditions. A unified shear deformation theory is used for analytical solution. The optimization process is carried out in order to obtain the minimum deflection parameters for Clamped-Free (C-F), Clamped-Clamped (C-C) and simply supported (S-S) boundary conditions under a uniform distributed load by use of genetic algorithm for a specific number of population and generation. Finally, among all possible combinations of layer thicknesses, the one giving the minimum deflection parameter and corresponding stacking sequence is chosen. The minimum values and corresponding stacking sequences are presented for different boundary conditions.
Źródło:
Advances in Science and Technology. Research Journal; 2015, 9, 26; 7-11
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Use Of Genetic Algorithms in Supply Chain Management. Literature Review and Current Trends
Использование генетических алгоритмов в управлении цепью поставок. Обзор литературы, актуальные тренды
Autorzy:
Stawiński, Piotr
Powiązania:
https://bibliotekanauki.pl/articles/1195683.pdf
Data publikacji:
2013
Wydawca:
Szkoła Główna Handlowa w Warszawie
Tematy:
управление цепью поставок
генетический алгоритм
оптимизация
supply chain management
genetic algorithm
optimization
Opis:
For the past few decades SCM has been one of the main objectives in research and practice. Since that time researchers have developed a lot of methods and procedures which optimized this process. To create an efficient supply chain network the resources and factories must be tightly integrated. The most supply chain network designs have multiple layers, members, periods, products, and comparative resources constraints exist between different layers. Supply chain networks design is related to the problems which are very popular in literature. The subject of this paper is to present the variants, configurations and parameters of genetic algorithm (GA) for solving supply chain network design problems. We focus on references from 2000 to 2011. Furthermore, current trends are introduced and discussed.
Уже несколько десятилетий управление цепью поставок (SCM) является одним из главных направлений исследований и практики. За это время были разработаны многие методы и процедуры оптимизации этого процесса. Чтобы создать эффективную сеть цепи поставок ресурсы и фабрики должны быть тесно интегрированы. SCM обращается к проблемам, которые очень популярны в литературе. Предметом настоящей работы является презентация вариантов конфигурации и параметров генетического алгоритма (GA), используемого для решения проблем с цепью поставок. В настоящей статье представлен обзор литературы за 2000–2011 гг. Креме того обсуждены здесь тренды, касающиеся проблематики SCM.
Źródło:
Edukacja Ekonomistów i Menedżerów; 2013, 27, 1; 167-184
1734-087X
Pojawia się w:
Edukacja Ekonomistów i Menedżerów
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Acoustical Assessment of Automotive Mufflers Using FEM, Neural Networks, and a Genetic Algorithm
Autorzy:
Chang, Y.-C.
Chiu, M.-C.
Wu, M.-R.
Powiązania:
https://bibliotekanauki.pl/articles/177901.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
acoustics
finite element method
genetic algorithm
muffler optimization
polynomial neural network model
Opis:
In order to enhance the acoustical performance of a traditional straight-path automobile muffler, a multi-chamber muffler having reverse paths is presented. Here, the muffler is composed of two internally parallel/extended tubes and one internally extended outlet. In addition, to prevent noise transmission from the muffler’s casing, the muffler’s shell is also lined with sound absorbing material. Because the geometry of an automotive muffler is complicated, using an analytic method to predict a muffler’s acoustical performance is difficult; therefore, COMSOL, a finite element analysis software, is adopted to estimate the automotive muffler’s sound transmission loss. However, optimizing the shape of a complicated muffler using an optimizer linked to the Finite Element Method (FEM) is time-consuming. Therefore, in order to facilitate the muffler’s optimization, a simplified mathematical model used as an objective function (or fitness function) during the optimization process is presented. Here, the objective function can be established by using Artificial Neural Networks (ANNs) in conjunction with the muffler’s design parameters and related TLs (simulated by FEM). With this, the muffler’s optimization can proceed by linking the objective function to an optimizer, a Genetic Algorithm (GA). Consequently, the discharged muffler which is optimally shaped will improve the automotive exhaust noise.
Źródło:
Archives of Acoustics; 2018, 43, 3; 517-529
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The concept of genetic programming in organizing internal transport processes
Autorzy:
Lewczuk, K.
Powiązania:
https://bibliotekanauki.pl/articles/223845.pdf
Data publikacji:
2015
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
scheduling
internal transport process
optimization
genetic algorithm
transport wewnętrzny
optymalizacja
programowanie genetyczne
Opis:
The paper presents proposition of using genetic algorithm to support organization of internal transport processes in logistics facilities. The organization of internal transport can be done through solving optimization task of scheduling internal transport process with allocation of human resources and equipment to the tasks. Internal transport process was defined and discussed as an object of organization. Precise methods of solving proposed optimization task were unable to give useful solutions according to the computational complexity of the problem, so heuristic genetic algorithm was proposed. The possible structures of chromosome representing feasible solutions, methods of generating initial population, base genetic operators: selection and inheritance, crossover, mutation and fixing of individuals were described. The main implementation difficulties, computational experiments and the scope of application of the algorithm were discussed.
Źródło:
Archives of Transport; 2015, 34, 2; 61-74
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of slender systems by means of genetic algorithms
Autorzy:
Sokół, K.
Kulawik, A.
Powiązania:
https://bibliotekanauki.pl/articles/973636.pdf
Data publikacji:
2014
Wydawca:
Politechnika Częstochowska. Wydawnictwo Politechniki Częstochowskiej
Tematy:
crack
genetic algorithm
optimization
slender system
pęknięcie
algorytm genetyczny
optymalizacja
układ smukły
Opis:
In this paper, the results of numerical studies on optimization of a geometrically nonlinear column with an internal crack by means of genetic algorithms are presented. The system is loaded by an axially applied external force P with a constant line of action. The presented problem is formulated on the basis of the principle of stationary total potential energy. The main purpose of this paper is to investigate an influence upon the localization of the crack and flexural rigidity ratio on critical loading of the system and to find an optimum localization of the crack in order to achieve high loading capacity. In order to calculate optimum values of these parameters the genetic algorithms are implemented into computer program. The artificial method of solution of the problem has been used due to the strongly nonlinear nature of the investigated problem.
Źródło:
Journal of Applied Mathematics and Computational Mechanics; 2014, 13, 1; 115-124
2299-9965
Pojawia się w:
Journal of Applied Mathematics and Computational Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Some efficient algorithms to deal with redundancy allocation problems
Autorzy:
Es-Sadqi, Mustapha
Idrissi, Abdellah
Benhassine, Ahlem
Powiązania:
https://bibliotekanauki.pl/articles/2141899.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
redundancy allocation problem
constraint programming
forward checking
optimization
genetic algorithm
top_k
Opis:
In this paper, we will discuss some algorithms in order to better optimize the problems of redundancy allocation in multi-state systems. The goal is to find the optimal configuration of the system that maximizes the availability and minimizes the investment cost. The availability will be evaluated using the universal generating function. In first step, our contribution consists in improving the genetic algorithm. In a second step, in the framework of the Constraint Programming, we propose a new method of optimization based on the Forward Checking as solver. Finally, we used the top-k method in our choice that helps us to get the best k elements from all possible values with highest availability. In comparison with the chosen study, our methods yield better results that satisfy the constraints of the problem in a shorter time.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 4; 48-57
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Evolutionary computing approaches to optimum design of fuzzy logic controller for a flexible robot system
Autorzy:
Subudhi, B.
Ranasingh, S.
Powiązania:
https://bibliotekanauki.pl/articles/230107.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
flexible manipulator
fuzzy logic
genetic algorithm
bacteria foraging optimization
tip position tracking
Opis:
This paper presents the design of a Fuzzy Logic Controller (FLC) whose parameters are optimized by using Genetic Algorithm (GA) and Bacteria Foraging Optimization (BFO) for tip position control of a single link flexible manipulator. The proposed FLC is designed by minimizing the fitness function, which is defined as a function of tip position error, through GA and BFO optimization algorithms achieving perfect tip position tracking of the single link flexible manipulator. Then the tip position responses obtained by using both the above controllers are compared to suggest the best controller for the tip position tracking.
Źródło:
Archives of Control Sciences; 2013, 23, 4; 395-412
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part II. Analysis of the results
Autorzy:
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/260079.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
set of non-dominated solutions
Opis:
Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimum structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from the four areas and giving an effective solution of the problem. Any significant progress towards solving the problem has not been obtained so far. An objective of the present paper was to develop an evolutionary algorithm for multiobjective optimization of the structural elements of large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in detail. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution, is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area for a high - speed vehicle-passenger catamaran structure, with taking into account several design variables such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinal and transversal members. Details of the computational models were kept at the level typical for conceptual design stage. Scantlings were analyzed by using the selected classification society rules. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm may be considered an efficient tool for multi-objective optimization of ship structures. The paper has been published in the three parts: Part I: Theoretical background on evolutionary multiobjective optimization, Part II: Computational simulations, and Part III: Analysis of the results.
Źródło:
Polish Maritime Research; 2011, 4; 3-13
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-objective optimization of high speed vehicle-passenger catamaran by genetic algorithm. Part I. Theoretical background on evolutionary multi objective optimization
Autorzy:
Sekulski, Z.
Powiązania:
https://bibliotekanauki.pl/articles/259303.pdf
Data publikacji:
2011
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
ship structure
multi-objective optimization
evolutionary algorithm
genetic algorithm
Pareto domination
set of non-dominated solutions
Opis:
Real ship structural design problems are usually characterized by presence of many conflicting objectives. Simultaneously, a complete definition of the optimal structural design requires a formulation of size-topology-shape-material optimization task unifying the optimization problems from these four areas and giving an effective solution of this problem. So far, a significant progress towards the solution of this problem has not been obtained. An objective of the present paper was to develop an evolutionary algorithm for multi-objective optimization of the structural elements of the large spatial sections of ships. Selected elements of the multi-criteria optimization theory have been presented in details. Methods for solution of the multi-criteria optimization problems have been discussed with the focus on the evolutionary optimization algorithms. In the paper an evolutionary algorithm where selection takes place based on the aggregated objective function combined with domination attributes as well as distance to the asymptotic solution is proposed and applied to solve the problem of optimizing structural elements with respect to their weight and surface area on a high speed vehicle-passenger catamaran structure with several design variables, such as plate thickness, scantlings of longitudinal stiffeners and transverse frames, and spacing between longitudinals and transversal members. Details of the computational models were at the level typical for conceptual design. Scantlings were analyzed using the selected rules of a classification society. The results of numerical experiments with the use of the developed algorithm are presented. They show that the proposed genetic algorithm can be an efficient multi-objective optimization tool for ship structures optimization. The paper will be published in three parts: Part I: Theoretical background on evolutionary multi-objective optimization, Part II: Computational investigations, and Part III: Analysis of the results.
Źródło:
Polish Maritime Research; 2011, 2; 3-18
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modelling Microcystis Cell Density in a Mediterranean Shallow Lake of Northeast Algeria (Oubeira Lake), Using Evolutionary and Classic Programming
Autorzy:
Arif, Salah
Djellal, Adel
Djebbari, Nawel
Belhaoues, Saber
Touati, Hassen
Guellati, Fatma Zohra
Bensouilah, Mourad
Powiązania:
https://bibliotekanauki.pl/articles/2174666.pdf
Data publikacji:
2023
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
microcystis cell density
Multiple Linear Regression
Support Vector Machine
Particle Swarm Optimization
Genetic Algorithm
Bird Swarm Algorithm
Opis:
Caused by excess levels of nutrients and increased temperatures, freshwater cyanobacterial blooms have become a serious global issue. However, with the development of artificial intelligence and extreme learning machine methods, the forecasting of cyanobacteria blooms has become more feasible. We explored the use of multiple techniques, including both statistical [Multiple Regression Model (MLR) and Support Vector Machine (SVM)] and evolutionary [Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Bird Swarm Algorithm (BSA)], to approximate models for the prediction of Microcystis density. The data set was collected from Oubeira Lake, a natural shallow Mediterranean lake in the northeast of Algeria. From the correlation analysis of ten water variables monitored, six potential factors including temperature, ammonium, nitrate, and ortho-phosphate were selected. The performance indices showed; MLR and PSO provided the best results. PSO gave the best fitness but all techniques performed well. BSA had better fitness but was very slow across generations. PSO was faster than the other techniques and at generation 20 it passed BSA. GA passed BSA a little further, at generation 50. The major contributions of our work not only focus on the modelling process itself, but also take into consideration the main factors affecting Microcystis blooms, by incorporating them in all applied models.
Źródło:
Geomatics and Environmental Engineering; 2023, 17, 2; 31--68
1898-1135
Pojawia się w:
Geomatics and Environmental Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The influence of the diversified passenger population on safe evacuation from a passenger ship
Wpływ zróżnicowania populacji pasażerów na bezpieczną ewakuację ze statku pasażerskiego
Autorzy:
Łozowicka, D.
Powiązania:
https://bibliotekanauki.pl/articles/359307.pdf
Data publikacji:
2010
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
ewakuacja
statki pasażerskie
algorytmy genetyczne
optymalizacja
evacuation modeling
passenger ships
genetic algorithm
optimization
Opis:
This article states theoretical assumptions for the method of identifying disadvantageous evacuation times from ships relating to diversified populations of passengers. The influence of age, sex and physical fitness of people is examined. The presented optimization uses the genetic algorithms method as well as Genetic Algorithm and Direct Search Toolbox included in Matlab software. Examples of calculations of the time of passenger evacuation from a passenger ship are given to verify the operation of the developed method.
W artykule podaje się teoretyczne założenia do metody poszukiwania niekorzystnych czasów ewakuacji ze statków pod kątem zróżnicowania populacji pasażerów. Analizuje się wpływ wieku, płci oraz predyspozycji fizycznych ludzi. Do optymalizacji wykorzystuje się metodę algorytmów genetycznych, a także Genetic Algorithm and Direct Search Toolbox programu Matlab. Podaje się przykładowe obliczenia czasu ewakuacji ze statku pasażerskiego w celu zweryfikowania poprawności działania opracowanej metody.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2010, 21 (93); 57-61
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Criteria 3-Dimension Bin Packing Problem
Autorzy:
Kacprzak, Ł.
Rudy, J.
Żelazny, D.
Powiązania:
https://bibliotekanauki.pl/articles/409522.pdf
Data publikacji:
2015
Wydawca:
Politechnika Poznańska. Wydawnictwo Politechniki Poznańskiej
Tematy:
bin packing problem
multi-criteria
genetic algorithm
simulated annealing
discrete optimization
Pareto efficiency
Opis:
In this paper a multi-criteria approach to the 3-dimensions bin packing problem is considered. The chosen maximization criteria are the number and the total volume of the boxes loaded into the container. Existing solution representation and decoding method are applied to the problem. Next, two metaheuristic algorithms, namely simulated annealing and genetic algorithm are developed using the TOPSIS method for solution evaluation. Both algorithms are then used to obtain approximations of the Pareto front for a set of benchmarks from the literature. Despite the fact that both criteria work in favor of each other, we managed to obtain multiple solutions in many cases, proving that lesser number of boxes can lead to better utilization of the container volume and vice versa. We also observed, that the genetic algorithms performs slightly better in our test both in the terms of hyper-volume indicator and number of non-dominated solutions.
Źródło:
Research in Logistics & Production; 2015, 5, 1; 85-94
2083-4942
2083-4950
Pojawia się w:
Research in Logistics & Production
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Algorytmy genetyczne w problemach optymalizacji
Genetic algorithms in optimization problems
Autorzy:
Rutczyńska-Wdowiak, K.
Powiązania:
https://bibliotekanauki.pl/articles/250078.pdf
Data publikacji:
2015
Wydawca:
Instytut Naukowo-Wydawniczy TTS
Tematy:
algorytm genetyczny
optymalizacja
funkcja Goldsteina-Price'a
genetic algorithm
optimization
Goldstein-Price function
Opis:
W pracy analizowano skuteczność i uniwersalność stosowania algorytmów genetycznych w wybranych zagadnieniach optymalizacji. Zaimplementowano algorytm genetyczny dla problemu minimalizacji złożonych, trudnych do optymalizacji funkcji Goldsteina-Price'a i funkcji grzbietu wielbłąda sześciogarbnego. Próbowano odpowiedzieć na pytanie, gdzie można stosować omawianą metodę sztucznej inteligencji, a gdzie lepiej zastosować metody klasyczne.
In this work the efficiency and universality of the use of genetic algorithms in selected issues of optimization was analyzed. Genetic algorithm for minimization of Goldstein-Price's function and function of back of camel was implemented. In this work was attempted to answer the question, where can apply this method of artificial intelligence, and where better to use classical methods.
Źródło:
TTS Technika Transportu Szynowego; 2015, 12; 1324-1326, CD
1232-3829
2543-5728
Pojawia się w:
TTS Technika Transportu Szynowego
Dostawca treści:
Biblioteka Nauki
Artykuł
Wyświetlanie 1-50 z 110

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