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Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling
A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introd...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4163327/ https://www.ncbi.nlm.nih.gov/pubmed/25243220 http://dx.doi.org/10.1155/2014/630280 |
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author | Luo, Qifang Zhou, Yongquan Xie, Jian Ma, Mingzhi Li, Liangliang |
author_facet | Luo, Qifang Zhou, Yongquan Xie, Jian Ma, Mingzhi Li, Liangliang |
author_sort | Luo, Qifang |
collection | PubMed |
description | A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. |
format | Online Article Text |
id | pubmed-4163327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-41633272014-09-21 Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling Luo, Qifang Zhou, Yongquan Xie, Jian Ma, Mingzhi Li, Liangliang ScientificWorldJournal Research Article A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. Hindawi Publishing Corporation 2014 2014-08-27 /pmc/articles/PMC4163327/ /pubmed/25243220 http://dx.doi.org/10.1155/2014/630280 Text en Copyright © 2014 Qifang Luo et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Luo, Qifang Zhou, Yongquan Xie, Jian Ma, Mingzhi Li, Liangliang Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling |
title | Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling |
title_full | Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling |
title_fullStr | Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling |
title_full_unstemmed | Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling |
title_short | Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling |
title_sort | discrete bat algorithm for optimal problem of permutation flow shop scheduling |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4163327/ https://www.ncbi.nlm.nih.gov/pubmed/25243220 http://dx.doi.org/10.1155/2014/630280 |
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