Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area
Facility layout problems deal with layout of facilities, machines, cells, or departments in a shop floor. This research has formulated unequal area stochastic dynamic facility layout problems in an open or wallless area in order to minimize the upper bound of the sum of the material handling costs,...
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myutmep.5486520201109T06:22:01Z Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 201511 Ali, Derakhshanasl TJ Mechanical engineering and machinery Facility layout problems deal with layout of facilities, machines, cells, or departments in a shop floor. This research has formulated unequal area stochastic dynamic facility layout problems in an open or wallless area in order to minimize the upper bound of the sum of the material handling costs, and the sum of the shifting costs in the whole time planning horizon. In addition, the areas and shapes of departments are fixed during the iteration of an algorithm and throughout the time horizon. In unequal area stochastic dynamic facility layout problems, there are several periods for the material flow among departments or product demand such that the material flow among departments or product demand is not stable in each period. In other words, the product demand is stochastic with a known expected value and standard deviation in each period. In this research, a new mixed integer nonlinear programming mathematical model was proposed for solving this type of problems. Particularly, they are nondeterministic polynomialtime hard and very complex, and exact methods could not solve them within a reasonable computational time. Therefore, metaheuristic algorithms and evolution strategies are needed to solve them. In this research, a modified covariance matrix adaptation evolution strategy algorithm was developed and the results were compared with two improved metaheuristic algorithms (improved particle swarm optimization and modified genetic algorithm). These two metaheuristic algorithms were developed and used to justify the efficiency of the proposed evolution strategy algorithm. The proposed algorithms applied four methods, which are (1) department swapping method, (2) local search method 1, (3) period swapping method, and (4) local search method 2, to prevent local optima and improve the quality of solutions for the problems. The proposed algorithms and the proposed mathematical model were validated using manual and graphical inspection methods, respectively. The trial and error method was applied to set the respective parametric values of the proposed algorithms in order to achieve better layouts. A real case and a theoretical problem were introduced to test the proposed algorithms. The results showed that the proposed covariance matrix adaptation evolution strategy has found better solutions in contrast to the proposed particle swarm optimization and genetic algorithm. 201511 Thesis http://eprints.utm.my/id/eprint/54865/ http://eprints.utm.my/id/eprint/54865/1/AliDerakhshanaslPFKM2015.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:96373 phd doctoral Universiti Teknologi Malaysia, Faculty of Mechanical Engineering Faculty of Mechanical Engineering 
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English 
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TJ Mechanical engineering and machinery 
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TJ Mechanical engineering and machinery Ali, Derakhshanasl Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 
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Facility layout problems deal with layout of facilities, machines, cells, or departments in a shop floor. This research has formulated unequal area stochastic dynamic facility layout problems in an open or wallless area in order to minimize the upper bound of the sum of the material handling costs, and the sum of the shifting costs in the whole time planning horizon. In addition, the areas and shapes of departments are fixed during the iteration of an algorithm and throughout the time horizon. In unequal area stochastic dynamic facility layout problems, there are several periods for the material flow among departments or product demand such that the material flow among departments or product demand is not stable in each period. In other words, the product demand is stochastic with a known expected value and standard deviation in each period. In this research, a new mixed integer nonlinear programming mathematical model was proposed for solving this type of problems. Particularly, they are nondeterministic polynomialtime hard and very complex, and exact methods could not solve them within a reasonable computational time. Therefore, metaheuristic algorithms and evolution strategies are needed to solve them. In this research, a modified covariance matrix adaptation evolution strategy algorithm was developed and the results were compared with two improved metaheuristic algorithms (improved particle swarm optimization and modified genetic algorithm). These two metaheuristic algorithms were developed and used to justify the efficiency of the proposed evolution strategy algorithm. The proposed algorithms applied four methods, which are (1) department swapping method, (2) local search method 1, (3) period swapping method, and (4) local search method 2, to prevent local optima and improve the quality of solutions for the problems. The proposed algorithms and the proposed mathematical model were validated using manual and graphical inspection methods, respectively. The trial and error method was applied to set the respective parametric values of the proposed algorithms in order to achieve better layouts. A real case and a theoretical problem were introduced to test the proposed algorithms. The results showed that the proposed covariance matrix adaptation evolution strategy has found better solutions in contrast to the proposed particle swarm optimization and genetic algorithm. 
format 
Thesis 
qualification_name 
Doctor of Philosophy (PhD.) 
qualification_level 
Doctorate 
author 
Ali, Derakhshanasl 
author_facet 
Ali, Derakhshanasl 
author_sort 
Ali, Derakhshanasl 
title 
Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 
title_short 
Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 
title_full 
Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 
title_fullStr 
Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 
title_full_unstemmed 
Improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 
title_sort 
improved covariance matrix evolution strategy algorithm for stochastic dynamic unequal area facility layouts in an open area 
granting_institution 
Universiti Teknologi Malaysia, Faculty of Mechanical Engineering 
granting_department 
Faculty of Mechanical Engineering 
publishDate 
2015 
url 
http://eprints.utm.my/id/eprint/54865/1/AliDerakhshanaslPFKM2015.pdf 
_version_ 
1747817743666642944 