A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop

Considering flow shop scheduling problem with more objectives, will help to make it more practical. For this purpose, we have intended both the makespan and total due date cost simultaneously. Total due date cost is included the sum of earliness and tardiness cost. In order to solve this problem, a...

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Main Authors:	N. Shahsavari Pour, M.H. Abolhasani Ashkezari, H. Mohammadi Andargoli
Format:	Article
Language:	English
Published:	Ayandegan Institute of Higher Education, 2013-03-01
Series:	International Journal of Research in Industrial Engineering
Subjects:	due date flow shop scheduling problem genetic algorithm makespan multi-objective tabu search
Online Access:	http://www.riejournal.com/article_47905_48c0a61270758bf4a0b1610336b5fd4c.pdf

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spelling	doaj-f90e7b7399e74fcab954869b472cdb902021-09-06T05:42:44ZengAyandegan Institute of Higher Education,International Journal of Research in Industrial Engineering2783-13372717-29372013-03-0121202947905A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow ShopN. Shahsavari Pour0M.H. Abolhasani Ashkezari1H. Mohammadi Andargoli2Department of Industrial Management, Vali-e-Asr University, Rafsanjan, IranDepartment of Industrial Engineering, Science and Research Branch, Islamic Azad University, Kerman, IranDepartment of Industrial Engineering, Science and Research Branch, Islamic Azad University, Kerman, IranConsidering flow shop scheduling problem with more objectives, will help to make it more practical. For this purpose, we have intended both the makespan and total due date cost simultaneously. Total due date cost is included the sum of earliness and tardiness cost. In order to solve this problem, a genetic algorithm is developed. In this GA algorithm, to further explore in solution space a Tabu Search algorithm is used. Also in selecting the new population, is used the concept of elitism to increase the chance of choosing the best sequence. To evaluate the performance of this algorithm and performing the experiments, it is coded in VBA. Experiments results and comparison with GA is indicated the high potential of this algorithm in solving the multi-objective problems.http://www.riejournal.com/article_47905_48c0a61270758bf4a0b1610336b5fd4c.pdfdue dateflow shop scheduling problemgenetic algorithmmakespanmulti-objectivetabu search
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	N. Shahsavari Pour M.H. Abolhasani Ashkezari H. Mohammadi Andargoli
spellingShingle	N. Shahsavari Pour M.H. Abolhasani Ashkezari H. Mohammadi Andargoli A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop International Journal of Research in Industrial Engineering due date flow shop scheduling problem genetic algorithm makespan multi-objective tabu search
author_facet	N. Shahsavari Pour M.H. Abolhasani Ashkezari H. Mohammadi Andargoli
author_sort	N. Shahsavari Pour
title	A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop
title_short	A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop
title_full	A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop
title_fullStr	A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop
title_full_unstemmed	A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop
title_sort	genetic algorithm coupled with tabu search for bi-objective permutation flow shop
publisher	Ayandegan Institute of Higher Education,
series	International Journal of Research in Industrial Engineering
issn	2783-1337 2717-2937
publishDate	2013-03-01
description	Considering flow shop scheduling problem with more objectives, will help to make it more practical. For this purpose, we have intended both the makespan and total due date cost simultaneously. Total due date cost is included the sum of earliness and tardiness cost. In order to solve this problem, a genetic algorithm is developed. In this GA algorithm, to further explore in solution space a Tabu Search algorithm is used. Also in selecting the new population, is used the concept of elitism to increase the chance of choosing the best sequence. To evaluate the performance of this algorithm and performing the experiments, it is coded in VBA. Experiments results and comparison with GA is indicated the high potential of this algorithm in solving the multi-objective problems.
topic	due date flow shop scheduling problem genetic algorithm makespan multi-objective tabu search
url	http://www.riejournal.com/article_47905_48c0a61270758bf4a0b1610336b5fd4c.pdf
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A Genetic Algorithm Coupled with Tabu Search for Bi-Objective Permutation Flow Shop

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