Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms
We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS) in the Flexible Manufacturing System (FMS) used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA), the Immune Genetic Algorit...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Abstract and Applied Analysis |
| Online Access: | http://dx.doi.org/10.1155/2013/634812 |
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| _version_ | 1832548782273724416 |
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| author | Kuo-Yang Wu Sendren Sheng-Dong Xu Tzong-Chen Wu |
| author_facet | Kuo-Yang Wu Sendren Sheng-Dong Xu Tzong-Chen Wu |
| author_sort | Kuo-Yang Wu |
| collection | DOAJ |
| description | We investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS) in the Flexible Manufacturing System (FMS) used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA), the Immune Genetic Algorithm (IGA), and the Particle Swarm Optimization (PSO) algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R) machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods. |
| format | Article |
| id | doaj-art-ba244d4683d746c0a869c65cfb81b26a |
| institution | Kabale University |
| issn | 1085-3375 1687-0409 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Abstract and Applied Analysis |
| spelling | doaj-art-ba244d4683d746c0a869c65cfb81b26a2025-02-03T06:13:09ZengWileyAbstract and Applied Analysis1085-33751687-04092013-01-01201310.1155/2013/634812634812Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary AlgorithmsKuo-Yang Wu0Sendren Sheng-Dong Xu1Tzong-Chen Wu2Department of Information Management, National Taiwan University of Science and Technology, Taipei 106, TaiwanGraduate Institute of Automation and Control, National Taiwan University of Science and Technology, Taipei 106, TaiwanDepartment of Information Management, National Taiwan University of Science and Technology, Taipei 106, TaiwanWe investigate the optimal scheduling of retrieval jobs for double-deep type Automated Storage and Retrieval Systems (AS/RS) in the Flexible Manufacturing System (FMS) used in modern industrial production. Three types of evolutionary algorithms, the Genetic Algorithm (GA), the Immune Genetic Algorithm (IGA), and the Particle Swarm Optimization (PSO) algorithm, are implemented to obtain the optimal assignments. The objective is to minimize the working distance, that is, the shortest retrieval time travelled by the Storage and Retrieval (S/R) machine. Simulation results and comparisons show the advantages and feasibility of the proposed methods.http://dx.doi.org/10.1155/2013/634812 |
| spellingShingle | Kuo-Yang Wu Sendren Sheng-Dong Xu Tzong-Chen Wu Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms Abstract and Applied Analysis |
| title | Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms |
| title_full | Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms |
| title_fullStr | Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms |
| title_full_unstemmed | Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms |
| title_short | Optimal Scheduling for Retrieval Jobs in Double-Deep AS/RS by Evolutionary Algorithms |
| title_sort | optimal scheduling for retrieval jobs in double deep as rs by evolutionary algorithms |
| url | http://dx.doi.org/10.1155/2013/634812 |
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