An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem
This paper deals with stochastic dynamic facility layout problem under demand uncertainty in terms of material flow between facilities. A robust approach suggests a robust layout in each period as the most frequent one falling within a prespecified percentage of the optimal solution for multiple sce...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2018-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2018/1529058 |
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| _version_ | 1832558057649864704 |
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| author | Yunfang Peng Tian Zeng Lingzhi Fan Yajuan Han Beixin Xia |
| author_facet | Yunfang Peng Tian Zeng Lingzhi Fan Yajuan Han Beixin Xia |
| author_sort | Yunfang Peng |
| collection | DOAJ |
| description | This paper deals with stochastic dynamic facility layout problem under demand uncertainty in terms of material flow between facilities. A robust approach suggests a robust layout in each period as the most frequent one falling within a prespecified percentage of the optimal solution for multiple scenarios. Mont Carlo simulation method is used to randomly generate different scenarios. A mathematical model is established to describe the dynamic facility layout problem with the consideration of transport device assignment. As a solution procedure for the proposed model, an improved adaptive genetic algorithm with population initialization strategy is developed to reduce the search space and improve the solving efficiency. Different sized instances are compared with Particle Swarm Optimization (PSO) algorithm to verify the effectiveness of the proposed genetic algorithm. The experiments calculating the cost deviation ratio under different fluctuation level show the good performance of the robust layout compared to the expected layout. |
| format | Article |
| id | doaj-art-ae1c8a0b81b44d08af5257127449f3a8 |
| institution | Kabale University |
| issn | 1026-0226 1607-887X |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-ae1c8a0b81b44d08af5257127449f3a82025-02-03T01:33:20ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2018-01-01201810.1155/2018/15290581529058An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout ProblemYunfang Peng0Tian Zeng1Lingzhi Fan2Yajuan Han3Beixin Xia4School of Management, Shanghai University, Shanghai 200444, ChinaSchool of Management, Shanghai University, Shanghai 200444, ChinaSchool of Management, Shanghai University, Shanghai 200444, ChinaSchool of Management, Shanghai University, Shanghai 200444, ChinaSchool of Management, Shanghai University, Shanghai 200444, ChinaThis paper deals with stochastic dynamic facility layout problem under demand uncertainty in terms of material flow between facilities. A robust approach suggests a robust layout in each period as the most frequent one falling within a prespecified percentage of the optimal solution for multiple scenarios. Mont Carlo simulation method is used to randomly generate different scenarios. A mathematical model is established to describe the dynamic facility layout problem with the consideration of transport device assignment. As a solution procedure for the proposed model, an improved adaptive genetic algorithm with population initialization strategy is developed to reduce the search space and improve the solving efficiency. Different sized instances are compared with Particle Swarm Optimization (PSO) algorithm to verify the effectiveness of the proposed genetic algorithm. The experiments calculating the cost deviation ratio under different fluctuation level show the good performance of the robust layout compared to the expected layout.http://dx.doi.org/10.1155/2018/1529058 |
| spellingShingle | Yunfang Peng Tian Zeng Lingzhi Fan Yajuan Han Beixin Xia An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem Discrete Dynamics in Nature and Society |
| title | An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem |
| title_full | An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem |
| title_fullStr | An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem |
| title_full_unstemmed | An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem |
| title_short | An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem |
| title_sort | improved genetic algorithm based robust approach for stochastic dynamic facility layout problem |
| url | http://dx.doi.org/10.1155/2018/1529058 |
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