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Tytuł:
Application of genetic algorithm for double-lap adhesive joint design
Autorzy:
Kurennov, Sergei
Barakhov, Konstantin
Polyakov, Olexander
Taranenko, Igor
Powiązania:
https://bibliotekanauki.pl/articles/27309876.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
adhesive joint
genetic algorithm
optimization
finite difference method
Goland-Reissner model
złącze klejowe
algorytm genetyczny
optymalizacja
metoda różnic skończonych
Model Golanda-Reissnera
Opis:
The problem of optimal design of symmetrical double-lap adhesive joint is considered. It is assumed that the main plate has constant thickness, while the thickness of the doublers can vary along the joint length. The optimization problem consists in finding optimal length of the joint and an optimal cross-section of the doublers, which provide minimum structural mass at given strength constraints. The classical Goland-Reissner model was used to describe the joint stress state. A corresponding system of differential equations with variable coefficients was solved using the finite difference method. Genetic optimization algorithm was used for numerical solution of the optimization problem. In this case, Fourier series were used to describe doubler thickness variation along the joint length. This solution ensures smoothness of the desired function. Two model problems were solved. It is shown that the length and optimal shape of the doubler depend on the design load.
Źródło:
Archive of Mechanical Engineering; 2023, LXX, 1; 27--42
0004-0738
Pojawia się w:
Archive of Mechanical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Calculation strength optimum of surgical robot effector for mechanical eigenproblems using FEM and genetic algorithm
Autorzy:
Ilewicz, Grzegorz
Powiązania:
https://bibliotekanauki.pl/articles/24201993.pdf
Data publikacji:
2023
Wydawca:
Politechnika Poznańska. Instytut Mechaniki Stosowanej
Tematy:
surgical robot
resonance phenomena
elastic buckling
optimization
genetic algorithm
FEM
robot chirurgiczny
zjawisko rezonansu
wyboczenie sprężyste
optymalizacja
algorytm genetyczny
MES
Opis:
It is essential to check whether the surgical robot end effector is safe to use due to phenomena such as linear buckling and mechanical resonance. The aim of this research is to build an multi criteria optimization model based on such criteria as the first natural frequency, buckling factor and mass, with the assumption of the basic constraint in the form of a safety factor. The calculations are performed for a serial structure of surgical robot end effector with six degrees of freedom ended with a scalpel. The calculation model is obtained using the finite element method. The issue of multi-criteria optimization is solved based on the response surface method, Pareto fronts and the genetic algorithm. The results section illustrates deformations of a surgical robot end effector occurring during the resonance phenomenon and the buckling deformations for subsequent values of the buckling coefficients. The dependencies of the geometrical dimensions on the criteria are illustrated with the continuous functions of the response surface, i.e. metamodels. Pareto fronts are illustrated, based on which the genetic algorithm finds the optimal quantities of the vector function. The conducted analyzes provide a basis for selecting surgical robot end effector drive systems from the point of view of their generated inputs.
Źródło:
Vibrations in Physical Systems; 2023, 34, 1; art. no. 2023106
0860-6897
Pojawia się w:
Vibrations in Physical Systems
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:
Comprehensive analysis of reclamation of spent lubricating oil using green solvent: RSM and ANN approach
Autorzy:
Sarkar, Sayantan
Datta, Deepshikha
Chowdhury, Somnath
Das, Bimal
Powiązania:
https://bibliotekanauki.pl/articles/2173421.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
modelling
optimization
extraction-flocculation
artificial neural network
genetic algorithm
modelowanie
optymalizacja
sztuczna sieć neuronowa
algorytm genetyczny
Opis:
Waste lubricating oil (WLO) is the most significant liquid hazardous waste, and indiscriminate disposal of waste lubricating oil creates a high risk to the environment and ecology. Present investigation emphasizes the re-refining of used automobile engine oil using the extraction-flocculation approach to reduce environmental hazards and convert the waste to energy. The extraction-flocculation process was modeled and optimized using response surface methodology (RSM), artificial neural network (ANN), and genetic algorithm (GA). The present study assessed parametric effects of refining time, refining temperature, solvent to waste oil ratio, and flocculant dosage. Experimental findings showed that the percentage of yield of recovered oil is to the tune of 86.13%. With the Central Composite Design approach, the maximum percentage of extracted oil is 85.95%, evaluated with 80 minutes of refining time, 50.17 C refining temperature, 7:1 solvent to waste oil ratio and flocculant dosage of 3 g/kg of solvent and 86.71% with 79.97 minutes refining time, 55.53 C refining temperature, 4.89:1 g/g solvent to waste oil ratio, 2.99 g/kg of flocculant concentration with Artificial Neural Network. A comparison shows that the ANN gives better results than the CCD approach. Physico-chemical properties of the recovered lube oil are comparable with the properties of fresh lubricating oil.
Źródło:
Chemical and Process Engineering; 2022, 43, 2; 119--135
0208-6425
2300-1925
Pojawia się w:
Chemical and Process Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of process parameters in turning of magnesium AZ91D alloy for better surface finish using genetic algorithm
Autorzy:
Pradeep Kumar, Madhesan
Venkatesan, Rajamanickam
Manimurugan, Manickam
Powiązania:
https://bibliotekanauki.pl/articles/2142864.pdf
Data publikacji:
2022
Wydawca:
Centrum Badań i Innowacji Pro-Akademia
Tematy:
genetic algorithm
magnesium alloy
turning
optimization
Pareto front
RSM
algorytm genetyczny
stopy magnezu
obracanie
optymalizacja
front Pareto
Opis:
This research examined at the optimum cutting parameters for producing minimum surface roughness and maximum Material Removal Rate (MRR) when turning magnesium alloy AZ91D. Cutting speed (m/min), feed (mm/rev), and cut depth (mm) have all been considered in the experimental study. To find the best cutting parameters, Taguchi's technique and Response Surface Methodology (RSM), an evolutionary optimization techniques Genetic Algorithm (GA) and Non-dominated Sorting Genetic Algorithm-II (NSGA-II) were employed. GA gives better results of 34.04% lesser surface roughness and 15.2% higher MRR values when compared with Taguchi method. The most optimal values of surface roughness and MRR is received in multi objective optimization NSGA-II were 0.7341 µm and 9460 mm3/min for the cutting parameters cutting speed at 140.73m/min, feed rate at 0.06mm/min and 0.99mm depth of cut. Multi objective NSGA-II optimization provides several non-dominated points on Pareto Front model that can be utilized as decision making for choice among objectives.
Źródło:
Acta Innovations; 2022, 43; 54-62
2300-5599
Pojawia się w:
Acta Innovations
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimization of the process of restoring the continuity of the WDS based on the matrix and genetic algorithm approach
Autorzy:
Antonowicz, Ariel
Urbaniak, Andrzej
Powiązania:
https://bibliotekanauki.pl/articles/2173692.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
WNTR
Water Network Tool for Resilience
aggregation of failures
water distribution system
EPANET Solver
Graph Searching Algorithms
genetic algorithm
optimization
post-disaster events
agregacja awarii
system dystrybucji wody
EPANET
algorytm wyszukiwania grafów
algorytm genetyczny
optymalizacja
wydarzenia po katastrofie
Opis:
The article discusses an example of the use of graph search algorithms with trace of water analysis and aggregation of failures in the occurrence of a large number of failures in the Water Supply System (WSS). In the event of a catastrophic situation, based on the Water Distribution System (WDS) network model, information about detected failures, the condition and location of valves, the number of repair teams, criticality analysis, the coefficient of prioritization of individual network elements, and selected objective function, the algorithm proposes the order of repairing the failures should be analyzed. The approach proposed by the authors of the article assumes the selection of the following objective function: minimizing the time of lack of access to drinking water (with or without prioritization) and minimizing failure repair time (with or without failure aggregation). The algorithm was tested on three different water networks (small, medium, and large numbers of nodes) and three different scenarios (different numbers of failures and valves in the water network) for each selected water network. The results were compared to a valve designation approach for closure using an adjacency matrix and a Strategic Valve Management Model (SVMM).
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 4; art. no. e141594
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optymalizacja ustawienia paneli PV z wykorzystaniem symulacji - „ClimateStudio” by Solemma
PV panel settings using simulation optimization - Climat Studio by Solemma
Autorzy:
Sitek, Michał
Powiązania:
https://bibliotekanauki.pl/articles/2064148.pdf
Data publikacji:
2022
Wydawca:
PWB MEDIA Zdziebłowski
Tematy:
fotowoltaika
symulacja
optymalizacja
algorytm genetyczny
budynek jednorodzinny
photovoltaics
simulation
optimization
genetic algorithm
one-family building
Opis:
Artykuł to studium przypadku doboru instalacji PV dla domu jednorodzinnego oraz optymalizacji położenia paneli na dachu płaskim z wykorzystaniem narzędzi projektowania generatywnego i optymalizacji genetycznej. Celem przeprowadzonych symulacji było wykazanie przydatności wybranego narzędzia do analiz zmiennych projektowanego systemu w relacji do zapotrzebowania na energię zdefiniowanego przez obecność i aktywności użytkowników obiektu.
This paper describes a case study of the selection of a PV installation for a single-family house and its configuration on a flat roof, using generative design and genetic optimisation tools. The purpose of the simulations carried out was to demonstrate the suitability of the chosen tool for the analysis of the variables of the designed system in relation to the energy demand defined by the presence and activity of the users of the facility.
Źródło:
Builder; 2022, 26, 3; 74--78
1896-0642
Pojawia się w:
Builder
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:
Solving scheduling problems with integrated online sustainability observation using heuristic optimization
Autorzy:
Burduk, Anna
Musiał, Kamil
Balashov, Artem
Batako, Andre
Safonyk, Andrii
Powiązania:
https://bibliotekanauki.pl/articles/2173719.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
production scheduling
sustainable development
genetic algorithm
meta-heuristics
intelligent optimization methods of production systems
tabu search
harmonogramowanie produkcji
zrównoważony rozwój
algorytm genetyczny
przeszukiwanie tabu
metaheurystyki
inteligentne metody optymalizacji systemów produkcyjnych
Opis:
The paper deals with the issue of production scheduling for various types of employees in a large manufacturing company where the decision-making process was based on a human factor and the foreman’s know-how, which was error-prone. Modern production processes are getting more and more complex. A company that wants to be competitive on the market must consider many factors. Relying only on human factors is not efficient at all. The presented work has the objective of developing a new employee scheduling system that might be considered a particular case of the job shop problem from the set of the employee scheduling problems. The Neuro-Tabu Search algorithm and the data gathered by manufacturing sensors and process controls are used to remotely inspect machine condition and sustainability as well as for preventive maintenance. They were used to build production schedules. The construction of the Neuro-Tabu Search algorithm combines the Tabu Search algorithm, one of the most effective methods of constructing heuristic algorithms for scheduling problems, and a self-organizing neural network that further improves the prohibition mechanism of the Tabu Search algorithm. Additionally, in the paper, sustainability with the use of Industry 4.0 is considered. That would make it possible to minimize the costs of employees’ work and the cost of the overall production process. Solving the optimization problem offered by Neuro-Tabu Search algorithm and real-time data shows a new way of production management.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2022, 70, 6; art. no. e143830
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The stress-minimizing hole in a shear-loaded elastic plate at a given energy increment
Autorzy:
Vigdergauz, S.
Powiązania:
https://bibliotekanauki.pl/articles/38694050.pdf
Data publikacji:
2022
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
2D elastostatic problem
Kolosov–Muskhelishvili potentials
stress concentration
factor
shape optimization
effective energy
extremal elastic structures
genetic algorithm
Opis:
Minimization of the peak tangential stresses around a single hole in an infinite 2D elastic plate under remote pure shear and a given hole-induced strain energy level is considered as a free-shape optimization problem under a physical constraint. It is solved by combining a genetic algorithm with the almost analytical, and hence highly accurate stress-strain solver for any finitely parameterized family of closed curves. The results obtained in wide ranges of the governing parameters are detailed and discussed. They may be applicable to the optimal holes design in constructive elements and dilute perforated structures. The current analysis extends the author’s previous publications, which were focused on the unconstrained shape optimization within the same setup.
Źródło:
Archives of Mechanics; 2022, 74, 2-3; 109-126
0373-2029
Pojawia się w:
Archives of Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A logistic optimization for the vehicle routing problem through a case study in the food industry
Autorzy:
Akpinar, Muhammet Enes
Powiązania:
https://bibliotekanauki.pl/articles/1835487.pdf
Data publikacji:
2021
Wydawca:
Wyższa Szkoła Logistyki
Tematy:
vehicle routing problem
time windows
optimization
metaheuristic algorithm
genetic algorithm
trasa pojazdu
okna czasowe
optymalizacja
algorytm metaheurystyczny
algorytm genetyczny
Opis:
In this study, the food delivery problem faced by a food company is discussed. There are seven different regions where the company serves food and a certain number of customers in each region. The time of requesting food for each customer varies according to the shift situation. This type of problem is referred to as a vehicle routing problem with time windows in the literature and the main aim of the study is to minimize the total travel distance of the vehicles. The second aim is to determine which vehicle will follow which route in the region by using the least amount of vehicle according to the desired mealtime. Methods: In this study, genetic algorithm methodology is used for the solution of the problem. Metaheuristic algorithms are used for problems that contain multiple combinations and cannot be solved in a reasonable time. Thus in this study, a solution to this problem in a reasonable time is obtained by using the genetic algorithm method. The advantage of this method is to find the most appropriate solution by trying possible solutions with a certain number of populations. Results: Different population sizes are considered in the study. 1000 iterations are made for each population. According to the genetic algorithm results, the best result is obtained in the lowest population size. The total distance has been shortened by about 14% with this method. Besides, the number of vehicles in each region and which vehicle will serve to whom has also been determined. This study, which is a real-life application, has provided serious profitability to the food company even from this region alone. Besides, there have been improvements at different rates in each of the seven regions. Customers' ability to receive service at any time has maximized customer satisfaction and increased the ability to work in the long term. Conclusions: The method and results used in the study were positive for the food company. However, the metaheuristic algorithm used in this study does not guarantee an optimal result. Therefore, mathematical models or simulation models can be considered in terms of future studies. Besides, in addition to the time windows problem, the pickup problem can also be taken into account and different solution proposals can be developed.
Źródło:
LogForum; 2021, 17, 3; 387-397
1734-459X
Pojawia się w:
LogForum
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Cross‐Comparison of Evolutionary Algorithms for Optimizing Design of Sustainable Supply Chain Network under Disruption Risks
Autorzy:
Al-Zuheri, Atiya
Powiązania:
https://bibliotekanauki.pl/articles/2023790.pdf
Data publikacji:
2021
Wydawca:
Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:
comparison
genetic algorithm
particle swarm optimization
sustainable supply chain design
disruption risk
porównanie
algorytm genetyczny
optymalizacja rojem cząstek
projektowanie zrównoważonego łańcucha dostaw
ryzyko zakłóceń
Opis:
Optimization of a sustainable supply chain network design (SSCND) is a complex decision-making process which can be done by the optimal determination of a set of decisions and constraints such as the selection of suppliers, transportation-related facilities and distribution centres. Different optimization techniques have been applied to handle various SSCND problems. Meta- heuristic algorithms are developed from these techniques that are commonly used to solving supply chain related problems. Among them, Genetic algorithms (GA) and particle swarm optimization (PSO) are implemented as optimization solvers to obtain supply network design decisions. This paper aims to compare the performance of these two evolutionary algorithms in optimizing such problems by minimizing the total cost that the system faces to potential disruption risks. The mechanism and implementation of these two evolutionary algorithms is presented in this paper. Also, using an optimization considers ordering, purchasing, inventory, transportation, and carbon tax cost, a numerical real-life case study is presented to demonstrate the validity of the effectiveness of these algorithms. A comparative study for the algorithms performance has been carried out based on the quality of the obtained solution and the results indicate that the GA performs better than PSO in finding lower-cost solution to the addressed SSCND problem. Despite a lot of research literature being done regarding these two algorithms in solving problems of SCND, few studies have compared the optimization performance between GA and PSO, especially the design of sustainable systems under risk disruptions.
Źródło:
Advances in Science and Technology. Research Journal; 2021, 15, 4; 342-351
2299-8624
Pojawia się w:
Advances in Science and Technology. Research Journal
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Genetic algorithm application for optimizing traffic signal timing reflecting vehicle emission intensity
Autorzy:
Hai, Dinh Tuan
Manh, Do Van
Nhat, Nguyen Minh
Powiązania:
https://bibliotekanauki.pl/articles/2098075.pdf
Data publikacji:
2021
Wydawca:
Politechnika Śląska. Wydawnictwo Politechniki Śląskiej
Tematy:
traffic signal optimization
heuristic solution
genetic algorithm
vehicle exhaust emission
intelligent transport system
optymalizacja sygnalizacji drogowej
rozwiązanie heurystyczne
algorytm genetyczny
emisja spalin pojazdu
inteligentny system transportowy
Opis:
Urbanization has created continuous growth in transportation demand, leading to serious issues, including infrastructure overload, disrupted traffic flow, and associated vehicular emissions. As a result, resolving these problems has become one of the primary missions of governments worldwide. The optimization of the traffic signal timing system is considered a promising approach to overcoming the negative consequences of increasing vehicle volume. In metropolises, oversaturated intersections, where the traffic density and vehicle exhaust emission levels are significant, have been considered as the priority to target. Several scientists have attempted to design traffic lights with the most appropriate timing. However, the majority of previous studies have not formed a comprehensive evaluation of essential factors, especially regarding the appropriate weighting of vehicle emission parameters. By assessing the all-inclusive relationship of critical elements with an emphasis on vehicle exhaust emissions, a performance index model using a genetic algorithm (GA) is established in this paper, demonstrated by data from a case study in Taiwan.
Źródło:
Transport Problems; 2021, 16, 1; 5--16
1896-0596
2300-861X
Pojawia się w:
Transport Problems
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:
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
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