A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem

Aimed at the no-idle flow-shop scheduling problem (NIFSP) with minimized makespan, a discrete sine optimization algorithm (DSOA) is proposed. Inspired by sine waveforms, the original sine optimization algorithm (SOA) is a global optimization algorithm, which uses the sine function to update the posi...

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Autores principales:	ZHAO Rui, GU Xingsheng
Formato:	article
Lenguaje:	ZH
Publicado:	Editorial Office of Journal of Shanghai Jiao Tong University 2020
Materias:	production scheduling sine optimization algorithm no-idle flow-shop scheduling problem (nifsp) iterated greedy algorithm makespan intelligent optimization algorithm local search Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989
Acceso en línea:	https://doaj.org/article/ab7673fabaf94e1ab023be89c5baba70
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spelling	oai:doaj.org-article:ab7673fabaf94e1ab023be89c5baba702021-11-04T09:34:51ZA Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem1006-246710.16183/j.cnki.jsjtu.2019.321https://doaj.org/article/ab7673fabaf94e1ab023be89c5baba702020-12-01T00:00:00Zhttp://xuebao.sjtu.edu.cn/CN/10.16183/j.cnki.jsjtu.2019.321https://doaj.org/toc/1006-2467Aimed at the no-idle flow-shop scheduling problem (NIFSP) with minimized makespan, a discrete sine optimization algorithm (DSOA) is proposed. Inspired by sine waveforms, the original sine optimization algorithm (SOA) is a global optimization algorithm, which uses the sine function to update the position of search agents. First, the update position strategy to adapt to the combinatorial optimization problem is redefined. An iterated greedy algorithm with a variable removing size is employed to update the position to enhance the exploration ability. Then, a crossover strategy and a selection strategy are applied to avoid the algorithm falling into local optimum. Next, to improve the exploitation ability of local search and the accuracy of the algorithm, an insertion-based local search scheme is applied in DSOA to search for a better solution around the current optimal solution. Finally, based on the Taillard benchmark, the simulation results of performance comparisons are presented. The experimental results demonstrate the effectiveness of the proposed DSOA algorithm for solving NIFSP.ZHAO RuiGU XingshengEditorial Office of Journal of Shanghai Jiao Tong Universityarticleproduction schedulingsine optimization algorithmno-idle flow-shop scheduling problem (nifsp)iterated greedy algorithmmakespanintelligent optimization algorithmlocal searchEngineering (General). Civil engineering (General)TA1-2040Chemical engineeringTP155-156Naval architecture. Shipbuilding. Marine engineeringVM1-989ZHShanghai Jiaotong Daxue xuebao, Vol 54, Iss 12, Pp 1291-1299 (2020)
institution	DOAJ
collection	DOAJ
language	ZH
topic	production scheduling sine optimization algorithm no-idle flow-shop scheduling problem (nifsp) iterated greedy algorithm makespan intelligent optimization algorithm local search Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989
spellingShingle	production scheduling sine optimization algorithm no-idle flow-shop scheduling problem (nifsp) iterated greedy algorithm makespan intelligent optimization algorithm local search Engineering (General). Civil engineering (General) TA1-2040 Chemical engineering TP155-156 Naval architecture. Shipbuilding. Marine engineering VM1-989 ZHAO Rui GU Xingsheng A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem
description	Aimed at the no-idle flow-shop scheduling problem (NIFSP) with minimized makespan, a discrete sine optimization algorithm (DSOA) is proposed. Inspired by sine waveforms, the original sine optimization algorithm (SOA) is a global optimization algorithm, which uses the sine function to update the position of search agents. First, the update position strategy to adapt to the combinatorial optimization problem is redefined. An iterated greedy algorithm with a variable removing size is employed to update the position to enhance the exploration ability. Then, a crossover strategy and a selection strategy are applied to avoid the algorithm falling into local optimum. Next, to improve the exploitation ability of local search and the accuracy of the algorithm, an insertion-based local search scheme is applied in DSOA to search for a better solution around the current optimal solution. Finally, based on the Taillard benchmark, the simulation results of performance comparisons are presented. The experimental results demonstrate the effectiveness of the proposed DSOA algorithm for solving NIFSP.
format	article
author	ZHAO Rui GU Xingsheng
author_facet	ZHAO Rui GU Xingsheng
author_sort	ZHAO Rui
title	A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem
title_short	A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem
title_full	A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem
title_fullStr	A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem
title_full_unstemmed	A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem
title_sort	discrete sine optimization algorithm for no-idle flow-shop scheduling problem
publisher	Editorial Office of Journal of Shanghai Jiao Tong University
publishDate	2020
url	https://doaj.org/article/ab7673fabaf94e1ab023be89c5baba70
work_keys_str_mv	AT zhaorui adiscretesineoptimizationalgorithmfornoidleflowshopschedulingproblem AT guxingsheng adiscretesineoptimizationalgorithmfornoidleflowshopschedulingproblem AT zhaorui discretesineoptimizationalgorithmfornoidleflowshopschedulingproblem AT guxingsheng discretesineoptimizationalgorithmfornoidleflowshopschedulingproblem
_version_	1718444982235299840

A Discrete Sine Optimization Algorithm for No-Idle Flow-Shop Scheduling Problem

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