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Tytuł:
Topology optimization of trusses using bars exchange method
Autorzy:
Bojczuk, D.
Rębosz-Kurdek, A.
Powiązania:
https://bibliotekanauki.pl/articles/202330.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
trusses
algorithm of optimization
optimal topologies
bars exchange
Opis:
The algorithm of optimization of trusses is presented in the paper, where for topology optimization the bars exchange method is used. In the first case, the problem aimed at cost minimization with a constraint set on global stiffness is formulated. In the second case, the problem of minimizing the cost function subjected to stress and cross-sectional area constraints is discussed and here the multiple-load case is taken into consideration. The conditions for introduction of topology modification and its acceptance are specified. The paper is illustrated with three examples.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2012, 60, 2; 185-189
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Synthesis and optimization of sequencing operation algorithm
Autorzy:
Ovsyak, O.
Petrushka, J.
Kozelko, M.
Powiązania:
https://bibliotekanauki.pl/articles/114365.pdf
Data publikacji:
2015
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
algebra of algorithms
operation of sequencing
synthesis of algorithm formula
optimization of algorithm formula
Opis:
Synthesis and optimization ways of sequencing operation applied in computer system, are described in the paper. The ways are general, and use sequencing and eliminating operations of algorithm algebra. They allow for automated synthesis of the sequencing operations. Optimization of algorithm formulas has been made on the basis of the properties of sequencing operations.
Źródło:
Measurement Automation Monitoring; 2015, 61, 10; 484-487
2450-2855
Pojawia się w:
Measurement Automation Monitoring
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:
A Short Introduction to Stochastic Optimization
Autorzy:
Ombach, Jerzy
Powiązania:
https://bibliotekanauki.pl/articles/1373633.pdf
Data publikacji:
2014
Wydawca:
Uniwersytet Jagielloński. Wydawnictwo Uniwersytetu Jagiellońskiego
Tematy:
global optimization
stochastic algorithm
random search
convergence of metaheuristics
Opis:
We present some typical algorithms used for finding global minimum/ maximum of a function defined on a compact finite dimensional set, discuss commonly observed procedures for assessing and comparing the algorithms’ performance and quote theoretical results on convergence of a broad class of stochastic algorithms.
Źródło:
Schedae Informaticae; 2014, 23; 9-20
0860-0295
2083-8476
Pojawia się w:
Schedae Informaticae
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:
A novel variant of the salp swarm algorithm for engineering optimization
Autorzy:
Jia, Fuyun
Luo, Sheng
Yin, Guan
Ye, Yin
Powiązania:
https://bibliotekanauki.pl/articles/23944824.pdf
Data publikacji:
2023
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
salp swarm algorithm
meta-heuristic algorithm
chaos theory
sine-cosine mechanism
quantum computation
optimization design of engineering
Opis:
There are many design problems need to be optimized in various fields of engineering, and most of them belong to the NP-hard problem. The meta-heuristic algorithm is one kind of optimization method and provides an effective way to solve the NP-hard problem. Salp swarm algorithm (SSA) is a nature-inspired algorithm that mimics and mathematically models the behavior of slap swarm in nature. However, similar to most of the meta-heuristic algorithms, the traditional SSA has some shortcomings, such as entrapment in local optima. In this paper, the three main strategies are adopted to strengthen the basic SSA, including chaos theory, sine-cosine mechanism and the principle of quantum computation. Therefore, the SSA variant is proposed in this research, namely SCQ-SSA. The representative benchmark functions are employed to test the performances of the algorithms. The SCQ-SSA are compared with the seven algorithms in high-dimensional functions (1000 dimensions), seven SSA variants and six advanced variants on benchmark functions, the experiment reveals that the SCQ-SSA enhances resulting precision and alleviates local optimal problems. Besides, the SCQ-SSA is applied to resolve three classical engineering problems: tubular column design problem, tension/compression spring design problem and pressure vessel design problem. The design results indicate that these engineering problems are optimized with high accuracy and superiority by the improved SSA. The source code is available in the URL: https://github.com/ye-zero/SCQSSA/tree/main/SCQ-SSA.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 3; 131--149
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Vessel route optimization to avoid risk of collision between carriers of dangerous goods and passenger vessels
Autorzy:
Boć, R.
Marcjan, K.
Przywarty, M.
Gucma, L.
Powiązania:
https://bibliotekanauki.pl/articles/135356.pdf
Data publikacji:
2016
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
carriage of dangerous goods
risk of collision
passenger ships
chemical tankers
optimization of ship routes
algorithm
Opis:
Abstract This article presents the underlying concepts of a mathematical model optimizing the routes of vessels carrying dangerous goods proceeding in the vicinity of passenger ferries. The method is based on the estimated risk of collision between a chemical tanker and a passenger vessel. Risk assessment was performed using three models. The first model determines the distance of the passing ships on the selected area on the basis of the AIS data. The second one is a stochastic model of navigational safety assessment, which provides statistical data on the probability of collision between the two chosen types of vessels. The third model determines the consequences of collisions between passenger ships and chemical tankers. The study defines the scope of the parameters affecting the objective function of vessel route optimization and their importance in the optimization problem.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2016, 48 (120); 65-70
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Development of a modified ant colony algorithm for order scheduling in food processing plants
Autorzy:
Korobiichuk, Igor
Hrybkov, Serhii
Seidykh, Olga
Ovcharuk, Volodymyr
Ovcharuk, Andrii
Powiązania:
https://bibliotekanauki.pl/articles/2204558.pdf
Data publikacji:
2022
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
order fulfillment planning
modified ant colony algorithm
efficiency of the algorithms
optimization
food industry
Opis:
This developed modified ant colony algorithm includes an additional improvement with local optimization methods, which reduces the time required to find a solution to the problem of optimization of combinatorial order sequence planning in a food enterprise. The planning problem requires consideration of a number of partial criteria, constraints, and an evaluation function to determine the effectiveness of the established version of the order fulfillment plan. The partial criteria used are: terms of storage of raw materials and finished products, possibilities of occurrence and processing of substandard products, terms of manufacturing orders, peculiarities of fulfillment of each individual order, peculiarities of use of technological equipment, expenses for storage and transportation of manufactured products to the end consumer, etc. The solution of such a problem is impossible using traditional methods. The proposed algorithm allows users to build and reconfigure plans, while reducing the time to find the optimum by almost 20% compared to other versions of algorithms.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2022, 16, 1; 53--61
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-Objective Optimization of Motor Vessel Route
Autorzy:
Marie, S.
Courteille, E.
Powiązania:
https://bibliotekanauki.pl/articles/117604.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
route planning
Optimization of Vessel Route
multi-objective optimization
Motor Vessel
Optimal Route
Multi-Objective Genetic Algorithm (MOGA)
Bézier Curve
MATLAB
Opis:
This paper presents an original method that allows computation of the optimal route of a motor vessel by minimizing its fuel consumption. The proposed method is based on a new and efficient meshing procedure that is used to define a set of possible routes. A consumption prediction tool has been developed in order to estimate the fuel consumption along a given trajectory. The consumption model involves the effects of the meteorological conditions, the shape of the hull and the power train characteristics. Pareto-optimization with a Multi-Objective Genetic Algorithm (MOGA) is taken as a framework for the definition and the solution of the multi-objective optimization problem addressed. The final goal of this study is to provide a decision helping tool giving the route that minimizes the fuel consumption in a limited or optimum time.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2009, 3, 2; 133-141
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Noise Elimination of Reciprocating Compressors Using FEM, Neural Networks Method, and the GA Method
Autorzy:
Chang, Y.-C.
Chiu, M.-C.
Xie, J.-L.
Powiązania:
https://bibliotekanauki.pl/articles/178126.pdf
Data publikacji:
2017
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
finite element method
polynomial neural network model
genetic algorithm
group method of data handling
reciprocating compressor
optimization
Opis:
Industry often utilizes acoustical hoods to block noise emitted from reciprocating compressors. However, the hoods are large and bulky. Therefore, to diminish the size of the compressor, a compact discharge muffler linked to the compressor outlet is considered. Because the geometry of a reciprocating compressor is irregular, COMSOL, a finite element analysis software, is adopted. In order to explore the acoustical performance, a mathematical model is established using a finite element method via the COMSOL commercialized package. Additionally, to facilitate the shape optimization of the muffler, a polynomial neural network model is adopted to serve as an objective function; also, a Genetic Algorithm (GA) is linked to the OBJ function. During the optimization, various noise abatement strategies such as a reverse expansion chamber at the outlet of the discharge muffler and an inner extended tube inside the discharge muffler, will be assessed by using the artificial neural network in conjunction with the GA optimizer. Consequently, the discharge muffler that is optimally shaped will decrease the noise of the reciprocating compressor.
Źródło:
Archives of Acoustics; 2017, 42, 2; 189-197
0137-5075
Pojawia się w:
Archives of Acoustics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Risk management in the allocation of vehicles to tasks in transport companies using a heuristic algorithm
Autorzy:
Izdebski, Mariusz
Powiązania:
https://bibliotekanauki.pl/articles/27311808.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
transport companies
allocation of vehicles
organization of transport
risk management
heuristic algorithm
ant algorithm
optimization
firmy transportowe
przydział pojazdów
organizacja transportu
zarządzanie ryzykiem
algorytm heurystyczny
algorytm mrówkowy
optymalizacja
Opis:
The work deals with the issue of assigning vehicles to tasks in transport companies, taking into account the minimization of the risk of dangerous events on the route of vehicles performing the assigned transport tasks. The proposed risk management procedure based on a heuristic algorithm reduces the risk to a minimum. The ant algorithm reduces it in the event of exceeding the limit, which differs from the classic methods of risk management, which are dedicated only to risk assessment. A decision model has been developed for risk management. The decision model considers the limitations typical of the classic model of assigning vehicles to tasks, e.g. window limits and additionally contains limitations on the acceptable risk on the route of vehicles' travel. The criterion function minimizes the probability of an accident occurring along the entire assignment route. The probability of the occurrence of dangerous events on the routes of vehicles was determined based on known theoretical distributions. The random variable of the distributions was defined as the moment of the vehicle's appearance at a given route point. Theoretical probability distributions were determined based on empirical data using the STATISTICA 13 package. The decision model takes into account such constraints as the time of task completion and limiting the acceptable risk. The criterion function minimizes the probability of dangerous events occurring in the routes of vehicles. The ant algorithm has been validated on accurate input data. The proposed ant algorithm was 95% effective in assessing the risk of adverse events in assigning vehicles to tasks. The algorithm was run 100 times. The designated routes were compared with the actual hours of the accident at the bottom of the measurement points. The graphical interpretation of the results is shown in the PTV Visum software. Verification of the algorithm confirmed its effectiveness. The work presents the process of building the algorithm along with its calibration.
Źródło:
Archives of Transport; 2023, 67, 3; 139--153
0866-9546
2300-8830
Pojawia się w:
Archives of Transport
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Organization of Municipal Waste Collection: the Decision Model
Organizacja zbiórki odpadów komunalnych: Model decyzyjny
Autorzy:
Izdebski, M.
Jacyna, M.
Powiązania:
https://bibliotekanauki.pl/articles/1813690.pdf
Data publikacji:
2018
Wydawca:
Politechnika Koszalińska. Wydawnictwo Uczelniane
Tematy:
organization of municipal waste collection
multi-criteria optimization
ant algorithm
organizacja zbiórki odpadów komunalnych
optymalizacja wielokryterialna
algorytm mrówkowy
Opis:
The paper presents the problem of organizing municipal waste collection from individual residents. A waste collection organization is defined as the designation of vehicle routes for a given collection. In order to solve this problem, a decision model for determining driving routes has been proposed. The organization of municipal waste collection may be considered in a single or multi-criteria approach. This study presents a collection of municipal waste in the context of a multi-criteria decision problem. In this work, the decision model of the municipal waste collection organization is based on multi-criteria optimization. In this case, the optimization algorithm was an ant algorithm. This algorithm has been specially modified to solve the problem of making decisions based on many criteria. The authors of this publication have not found application of this approach and this algorithm in the literature to designate the municipal waste collection organization. The municipal waste collection organization is a complex decision problem and refers to the traveling salesman problem. This problem belongs to NP-hard problems. To solve the problem of the traveling salesman, a heuristic algorithm should be applied. Fast time of generating the result by the ant algorithm is its main feature, which is desirable in the process of designating the municipal waste collection organization. This process depends on many factors, e.g. vehicle capacity, size of tasks. The algorithm for determining this type of problem must be adapted to frequent changes of these factors and quick generation of solutions. The time of solution generation plays the most important role in municipal companies. The ant algorithm generates results in a quick way and therefore this algorithm was chosen in this problem. The presented decision model concerns the collection of waste from individual residents. The car visits the loading points (inhabitants) and collects waste. The main goal is to designate this route. This fact additionally emphasizes the use of the heuristic algorithm in this problem. The work defines the mathematical model of the problem of municipal waste collection, the input data entered into the model are given, e.g. distances between objects of the transport network have been defined, driving times between these objects are given, loading times, unloading of waste, crossing time. The decision variable defines the connection between individual network objects implemented by the vehicle in a given route. Decision variables are binary type. Limitations have been introduced for working time and for the capacity of vehicles that collect waste. The criteria functions concern the minimization of the time of completion of all routes and the costs of fuel consumption. In order to check the correctness of the ant algorithm, its results were compared with random values. The ant algorithm in each case generated a better solution than a random algorithm. It should be emphasized that the form algorithm belongs to heuristic algorithms. The solution generated by these algorithms for complex decision problems is a suboptimal solution. However, taking into account the complexity of the municipal waste collection organization, the solution is accepted from a practical point of view.
W pracy przedstawiono problem organizacji zbiórki odpadów komunalnych od indywidualnych mieszkańców. Organizacja zbiórki odpadów jest zdefiniowana jako wyznaczenie tras jazdy pojazdów realizujących daną zbiórkę. W celu rozwiązania tego problemu zaproponowano model decyzyjny wyznaczania tras jazdy pojazdów. Organizacja zbiórki odpadów komunalnych może być rozpatrywany w ujęciu jedno lub wielokryterialnym. W niniejszym opracowaniu przedstawiono zbiórkę odpadów komunalnych w kontekście wielokryterialnego problemu decyzyjnego. W niniejszej pracy model decyzyjny organizacji zbiórki odpadów komunalnych opiera się na optymalizacji wielokryterialnej. W tym przypadku algorytm optymalizacji był algorytmem mrówkowym. Algorytm ten został specjalnie zmodyfikowany w celu rozwiązania problemu podejmowania decyzji w oparciu o wiele kryteriów. Autorzy tej publikacji nie znaleźli zastosowania tego podejścia i tego algorytmu w literaturze do wyznaczenia organizacji zbiórki odpadów komunalnych. Organizacja zbiórki odpadów komunalnych jest złożonym problemem decyzyjnym i odnosi się do problemu komiwojażera. Problem ten należy do problemów NP-trudnych. Aby rozwiązać problem komiwojażera, należy zastosować algorytm heurystycznych. Szybki czas generowania wyniku przez algorytm mrówkowy jest jego główną cechą, co jest pożądane w procesie wyznaczania organizacji zbiórki odpadów komunalnych. Proces ten zależy od wielu czynników, np. pojemność pojazdów, wielkość zadań. Algorytm wyznaczania tego typu problemu musi być dostosowany do częstych zmian tych czynników i szybkiego generowania rozwiązań. W firmach komunalnych najważniejszą rolę odgrywa czas generowania rozwiązania. Algorytm mrówkowy generuje wyniki w szybki sposób i dlatego ten algorytm został wybrany w tym problemie. Przedstawiony model decyzyjny dotyczy zbiórki odpadów od poszczególnych mieszkańców. Samochód odwiedza punkty załadunku (mieszkańców) i zbiera odpady. Głównym celem jest wyznaczenie tej trasy. Fakt ten dodatkowo podkreśla zastosowanie algorytmu heurystycznego w tym problemie. W pracy zdefiniowano model matematyczny problemu zbiórki odpadów komunalnych, podano dane wejściowe wprowadzane do modelu np. zdefiniowano odległości pomiędzy obiektami sieci transportowej, podano czasy jazdy pomiędzy tymi obiektami, czasy załadunku, wyładunku odpadów, czas przejazdu przez skrzyżowania. Zmienna decyzyjna określa połączenie pomiędzy poszczególnymi obiektami sieci realizowane przez pojazd w danej trasie. Zmienne decyzyjne są typu binarnego. Wprowadzono ograniczenia na czas pracy oraz na pojemność pojazdów realizujących zbiórkę odpadów. Funkcje kryteriów dotyczą minimalizacji czasu realizacji wszystkich tras oraz kosztów zużycia paliwa. W pracy szczegółowo scharakteryzowano algorytm mrówkowy rozwiązujący wielokryterialny problem decyzyjny zbiórki odpadów komunalnych. W celu sprawdzenia poprawności algorytmu mrówkowego jego wyniki porównano z wartościami losowymi. Algorytm mrówkowy w każdym przypadku generował lepsze rozwiązanie niż losowy algorytm. Należy podkreślić, że algorytm mrówkowy należy do algorytmów heurystycznych. Rozwiązanie wygenerowane przez te algorytmy dla złożonych problemów decyzyjnych jest rozwiązaniem nieoptymalnym. Biorąc jednak pod uwagę złożoność organizacji zbiórki odpadów komunalnych, rozwiązanie jest akceptowane z praktycznego punktu widzenia.
Źródło:
Rocznik Ochrona Środowiska; 2018, Tom 20, cz. 1; 919-933
1506-218X
Pojawia się w:
Rocznik Ochrona Środowiska
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Numeryczna optymalizacja profili śmigłowcowych oparta na algorytmie genetycznym z uwzględnieniem kryteriów bazujących na niestacjonarnych charakterystykach aerodynamicznych
Numerical optimization rotorcraft blade airfoils based on genetic algorithm and unstedy aerodynamic criteria
Autorzy:
Stalewski, W.
Powiązania:
https://bibliotekanauki.pl/articles/212749.pdf
Data publikacji:
2006
Wydawca:
Sieć Badawcza Łukasiewicz - Instytut Lotnictwa
Tematy:
numeryczna optymalizacja profili śmigłowców
algorytm genetyczny
niestacjonarne charakterystyki aerodynamiczne
numerical optimization of rotorcraft blade
genetic algorithm
areodynamic criteria
Opis:
W pracy przedstawiono metodę numerycznej optymalizacji profili lotniczych, ze szczególnym uwzględnieniem profili łopat wirnika nośnego śmigłowca. Metoda bazuje na algorytmie genetycznym. Optymalizacja realizowana jest poprzez symulację procesów ewolucji gatunków regulowanych prawami doboru naturalnego. Wielokryterialny algorytm genetyczny adaptowano na przypadek optymalizacji profili lotniczych. Opracowano wyspecjalizowany generator kształtu profili a także metodę analizy niestacjonarnego, transonicznego opływu profilu z uwzględnieniem silnego oddziaływania niestacjonarnej warstwy przyściennej. W oparciu o opracowane moduły obliczeniowe powstał pakiet oprogramowania OGA pozwalający rozwiązywać szeroką klasę zagadnień z zakresu wielokryterialnej optymalizacji profili śmigłowcowych. Przedstawiono wyniki obliczeń testowych wykonanych za pomocą opracowanego pakietu.
The optimization methodology of rotorcraft airfoils was presented. The methodology is based on the multi-objectiye genetic algorithm, where the process of optimization imitates the real processes of natural selection and heredity observed in lively nature. Basing on the worked out methodology the optimization software package was developed. This package enables a computational design of airfoils, which have the best aerodynamic properties with regard to given criteria. The multi-objective optimization with additional aerodynamic and geometrie constraints was applied. The specialized airfoil shape parameterization was worked out to get the wide class of airfoil geometry. The optimization criteria are directed to reąuirements and flow conditions specific to rotorcraft airfoils. In particular, the criteria are evaluated basing on unsteady aerodynamic characteristics that correspond to unsteady flow around rotor blades of rotorcraft in flight. The method of calculation of the unsteady, transonic flow with unsteady boundary layer analysis was developed. The method is used to evaluate both unsteady and steady aerodynamic objectives and constraints. Additionally, the several external codes were included inthe package, to get the wide possibilities of steady aerodynamic criteria formulation. The thorough verification of presented optimization software package was performed. The results confirmed the proper work of the package as well as its wide possibilities of use as the tool supporting the aerodynamic design.
Źródło:
Prace Instytutu Lotnictwa; 2006, 1-2 (184-185); 54-64
0509-6669
2300-5408
Pojawia się w:
Prace Instytutu Lotnictwa
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Zastosowanie półautomatycznego algorytmu doboru optymalnej liczby i położenia odwiertów wydobywczych
Semi-Automatic Algorithm for Optimal Production Well Placement
Autorzy:
Łętkowski, P.
Powiązania:
https://bibliotekanauki.pl/articles/1835267.pdf
Data publikacji:
2018
Wydawca:
Instytut Nafty i Gazu - Państwowy Instytut Badawczy
Tematy:
optymalizacja
algorytm nietoperza
położenie odwiertów
NPV
eksploatacja
algorytmy rojowe
optimization
bat algorithm
location of wells
exploitation
swarm algorithms
Opis:
Artykuł poświęcono zastosowaniu tzw. algorytmu nietoperza do rozwiązania problemu określenia optymalnej liczby i położenia odwiertów wydobywczych. W procesie optymalizacji jako funkcję celu wykorzystano bieżącą wartość netto (ang. net present value – NPV). Testy zbudowanego algorytmu przeprowadzono na przykładzie modelu symulacyjnego złoża PUNQ-S3, dostępne- go na zasadach open source. Zastosowany algorytm został wyposażony w dodatkowe mechanizmy zwiększające jego efektywność: mechanizm próbkowania sześcianu łacińskiego (ang. Latin hypercube sampling – LHS) oraz mechanizm eliminowania położeń odwiertów poza modelem. Przeprowadzone testy wskazują na bardzo dobrą zbieżność zbudowanego algorytmu w procesie optymalizacji.
The article is devoted to the application of the so-called bat algorithm to solve the problem of determining the optimum number and location of production wells. This algorithm was proposed by Yang in 2010, and since then has been successfully used in solving both theoretical and practical optimization problems. The method belongs to a group of swarm optimization methods and in searching for the best solution, the algorithm uses a mechanism of echolocation, similar to the one used by a herd of bats. The current net present value (NPV) was used as a target function in the optimization process. The algorithm was tested on the example of the simulation model of the PUNQ-S3 reservoir available on an OpenSource basis. The applied algorithm was equipped with additional mechanisms increasing its effectiveness: Latin Hypercube Sampling (LHS) algorithm and the mechanism eliminating the locations of wells outside the operational area of the model. The first of the applied improvements ensures a better starting point for the proper optimization process, which significantly improves the convergence of the whole algorithm. The latter mechanism solves a problem specific to the issue in question.
Źródło:
Nafta-Gaz; 2018, 74, 8; 598-605
0867-8871
Pojawia się w:
Nafta-Gaz
Dostawca treści:
Biblioteka Nauki
Artykuł
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