Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure

In order to solve the scheduling problem of aircraft moving assembly line in uncertainty environment, this paper proposes a perceptron-dependent fruit fly optimization algorithm(PDFOA) to generate the assembly scheduling template with strong robustness. The proposed PDFOA, taking the fruit fly optim...

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Auteurs principaux:	FANG Jia, LU Zhiqiang
Format:	article
Langue:	ZH
Publié:	Editorial Office of Journal of Shanghai Jiao Tong University 2020
Sujets:	failure and repair of equipments fruit fly optimization algorithm proactive scheduling sampling simulation robust baseline scheduling Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989
Accès en ligne:	https://doaj.org/article/2e9c04bebbbd48c6bbf05c74494ba5d6
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id	oai:doaj.org-article:2e9c04bebbbd48c6bbf05c74494ba5d6
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spelling	oai:doaj.org-article:2e9c04bebbbd48c6bbf05c74494ba5d62021-11-04T09:34:51ZModeling and Optimization of Robust Scheduling Template Considering Equipment Failure1006-246710.16183/j.cnki.jsjtu.2019.146https://doaj.org/article/2e9c04bebbbd48c6bbf05c74494ba5d62020-12-01T00:00:00Zhttp://xuebao.sjtu.edu.cn/CN/10.16183/j.cnki.jsjtu.2019.146https://doaj.org/toc/1006-2467In order to solve the scheduling problem of aircraft moving assembly line in uncertainty environment, this paper proposes a perceptron-dependent fruit fly optimization algorithm(PDFOA) to generate the assembly scheduling template with strong robustness. The proposed PDFOA, taking the fruit fly optimization algorithm as the basis, designs narrow-field osphresis-search operation and narrow-field vision-search operation which is helpful for searching and choosing neighborhood solutions. Simultaneously, the PDFOA sets up a memory library to enhance the global search ability. Finally, simulation experiments are conducted using different testing samples on different job scales. The proposed PDFOA is compared with tabu search, the genetic algorithm and the immune particle swarm optimization algorithm. The results demonstrate the effectiveness of the PDFOA.FANG JiaLU ZhiqiangEditorial Office of Journal of Shanghai Jiao Tong Universityarticlefailure and repair of equipmentsfruit fly optimization algorithmproactive schedulingsampling simulationrobust baseline schedulingEngineering (General). Civil engineering (General)TA1-2040Chemical engineeringTP155-156Naval architecture. Shipbuilding. Marine engineeringVM1-989ZHShanghai Jiaotong Daxue xuebao, Vol 54, Iss 12, Pp 1278-1290 (2020)
institution	DOAJ
collection	DOAJ
language	ZH
topic	failure and repair of equipments fruit fly optimization algorithm proactive scheduling sampling simulation robust baseline scheduling Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989
spellingShingle	failure and repair of equipments fruit fly optimization algorithm proactive scheduling sampling simulation robust baseline scheduling Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989 FANG Jia LU Zhiqiang Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure
description	In order to solve the scheduling problem of aircraft moving assembly line in uncertainty environment, this paper proposes a perceptron-dependent fruit fly optimization algorithm(PDFOA) to generate the assembly scheduling template with strong robustness. The proposed PDFOA, taking the fruit fly optimization algorithm as the basis, designs narrow-field osphresis-search operation and narrow-field vision-search operation which is helpful for searching and choosing neighborhood solutions. Simultaneously, the PDFOA sets up a memory library to enhance the global search ability. Finally, simulation experiments are conducted using different testing samples on different job scales. The proposed PDFOA is compared with tabu search, the genetic algorithm and the immune particle swarm optimization algorithm. The results demonstrate the effectiveness of the PDFOA.
format	article
author	FANG Jia LU Zhiqiang
author_facet	FANG Jia LU Zhiqiang
author_sort	FANG Jia
title	Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure
title_short	Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure
title_full	Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure
title_fullStr	Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure
title_full_unstemmed	Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure
title_sort	modeling and optimization of robust scheduling template considering equipment failure
publisher	Editorial Office of Journal of Shanghai Jiao Tong University
publishDate	2020
url	https://doaj.org/article/2e9c04bebbbd48c6bbf05c74494ba5d6
work_keys_str_mv	AT fangjia modelingandoptimizationofrobustschedulingtemplateconsideringequipmentfailure AT luzhiqiang modelingandoptimizationofrobustschedulingtemplateconsideringequipmentfailure
_version_	1718444949671772160

Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure

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