An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II

Improving the performance of manufacturing systems is a vital issue in today’s rival market. For this purpose, during the last decade, scientists have considered more than one objective function while scheduling a production line. This paper develops a 4-phased fuzzy framework to identify effective...

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Main Authors: Delgoshaei, Aidin, Mohd Ariffin, Mohd Khairol Anuar, Leman, Zulkiflle
Format: Article
Published: Multidisciplinary Digital Publishing Institute 2022
Online Access:http://psasir.upm.edu.my/id/eprint/100231/
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author Delgoshaei, Aidin
Mohd Ariffin, Mohd Khairol Anuar
Leman, Zulkiflle
author_facet Delgoshaei, Aidin
Mohd Ariffin, Mohd Khairol Anuar
Leman, Zulkiflle
author_sort Delgoshaei, Aidin
building UPM Institutional Repository
collection Online Access
description Improving the performance of manufacturing systems is a vital issue in today’s rival market. For this purpose, during the last decade, scientists have considered more than one objective function while scheduling a production line. This paper develops a 4-phased fuzzy framework to identify effective factors, determine their weights on multi-objective functions, and, accordingly, schedule manufacturing systems in a fuzzy environment. The aim is to optimize product completion time and operational and product defect costs in a job-shop-based multi-objective fuzzy scheduling problem. In the first and second phases of the proposed framework, it was shown that the existing uncertainty of the internal factors for the studied cases causes the weights of factors to change up to 44.5%. Then, a fuzzy-weighted NSGA-II is proposed (FW-NSGA-II) to address the developed Non-linear Fuzzy Multi-objective Dual resource-constrained scheduling problem. Comparing the outcomes of the proposed method with other solving algorithms, such as the Sine Cosine Algorithm, Simulated Annealing, Tabu Search, and TLBO heuristic, using seven series of comprehensive computational experiments, indicates the superiority of the proposed framework in scheduling manufacturing systems. The outcomes indicated that using the proposed method for the studied cases saved up to 5% in the objective function for small-scale, 11.2% for medium-scale, and 3.8% for large-scale manufacturing systems. The outcomes of this study can help production planning managers to provide more realistic schedules by considering fuzzy factors in their manufacturing systems. Further investigating the proposed method for dynamic product conditions is another direction for future research.
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institution Universiti Putra Malaysia
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spelling upm-1002312024-07-11T04:07:37Z http://psasir.upm.edu.my/id/eprint/100231/ An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II Delgoshaei, Aidin Mohd Ariffin, Mohd Khairol Anuar Leman, Zulkiflle Improving the performance of manufacturing systems is a vital issue in today’s rival market. For this purpose, during the last decade, scientists have considered more than one objective function while scheduling a production line. This paper develops a 4-phased fuzzy framework to identify effective factors, determine their weights on multi-objective functions, and, accordingly, schedule manufacturing systems in a fuzzy environment. The aim is to optimize product completion time and operational and product defect costs in a job-shop-based multi-objective fuzzy scheduling problem. In the first and second phases of the proposed framework, it was shown that the existing uncertainty of the internal factors for the studied cases causes the weights of factors to change up to 44.5%. Then, a fuzzy-weighted NSGA-II is proposed (FW-NSGA-II) to address the developed Non-linear Fuzzy Multi-objective Dual resource-constrained scheduling problem. Comparing the outcomes of the proposed method with other solving algorithms, such as the Sine Cosine Algorithm, Simulated Annealing, Tabu Search, and TLBO heuristic, using seven series of comprehensive computational experiments, indicates the superiority of the proposed framework in scheduling manufacturing systems. The outcomes indicated that using the proposed method for the studied cases saved up to 5% in the objective function for small-scale, 11.2% for medium-scale, and 3.8% for large-scale manufacturing systems. The outcomes of this study can help production planning managers to provide more realistic schedules by considering fuzzy factors in their manufacturing systems. Further investigating the proposed method for dynamic product conditions is another direction for future research. Multidisciplinary Digital Publishing Institute 2022-12-05 Article PeerReviewed Delgoshaei, Aidin and Mohd Ariffin, Mohd Khairol Anuar and Leman, Zulkiflle (2022) An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II. Mathematics, 10 (23). art. no. 4607. pp. 1-28. ISSN 2227-7390 https://www.mdpi.com/2227-7390/10/23/4607 10.3390/math10234607
spellingShingle Delgoshaei, Aidin
Mohd Ariffin, Mohd Khairol Anuar
Leman, Zulkiflle
An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II
title An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II
title_full An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II
title_fullStr An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II
title_full_unstemmed An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II
title_short An effective 4–phased framework for scheduling job-shop manufacturing systems using weighted NSGA-II
title_sort effective 4–phased framework for scheduling job-shop manufacturing systems using weighted nsga-ii
url http://psasir.upm.edu.my/id/eprint/100231/
http://psasir.upm.edu.my/id/eprint/100231/
http://psasir.upm.edu.my/id/eprint/100231/