Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization

Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization

Recently, interest in integrated assembly sequence planning (ASP) and assembly line balancing (ALB) began to pick up because of its numerous benefits, such as the larger search space that leads to better solution quality, reduced error rate in planning, and expedited product time-to-market. However,...

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Main Authors: M. F. F., Ab Rashid, Tiwari, Ashutosh, Hutabarat, Windo
Format: Article
Language:English
Published: Cambridge University Press 2019
Subjects:
TS Manufactures
Online Access:http://umpir.ump.edu.my/id/eprint/25651/
http://umpir.ump.edu.my/id/eprint/25651/
http://umpir.ump.edu.my/id/eprint/25651/1/2019%20MM-ASPALB%20AIEDAM.pdf
id ump-25651
recordtype eprints
spelling ump-256512019-11-21T02:56:23Z http://umpir.ump.edu.my/id/eprint/25651/ Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization M. F. F., Ab Rashid Tiwari, Ashutosh Hutabarat, Windo TS Manufactures Recently, interest in integrated assembly sequence planning (ASP) and assembly line balancing (ALB) began to pick up because of its numerous benefits, such as the larger search space that leads to better solution quality, reduced error rate in planning, and expedited product time-to-market. However, existing research is limited to the simple assembly problem that only runs one homogenous product. This paper therefore models and optimizes the integrated mixed-model ASP and ALB using Multi-objective Discrete Particle Swarm Optimization (MODPSO) concurrently. This is a new variant of the integrated assembly problem. The integrated mixed-model ASP and ALB is modeled using task-based joint precedence graph. In order to test the performance of MODPSO to optimize the integrated mixed-model ASP and ALB, an experiment using a set of 51 test problems with different difficulty levels was conducted. Besides that, MODPSO coefficient tuning was also conducted to identify the best setting so as to optimize the problem. The results from this experiment indicated that the MODPSO algorithm presents a significant improvement in term of solution quality toward Pareto optimal and demonstrates the ability to explore the extreme solutions in the mixed-model assembly optimization search space. The originality of this research is on the new variant of integrated ASP and ALB problem. This paper is the first published research to model and optimize the integrated ASP and ALB research for mixed-model assembly problem. Cambridge University Press 2019-08-01 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/25651/1/2019%20MM-ASPALB%20AIEDAM.pdf M. F. F., Ab Rashid and Tiwari, Ashutosh and Hutabarat, Windo (2019) Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization. Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 33 (3). pp. 332-345. ISSN 1469-1760 https://doi.org/10.1017/S0890060419000131
repository_type Digital Repository
institution_category Local University
institution Universiti Malaysia Pahang
building UMP Institutional Repository
collection Online Access
language English
topic TS Manufactures
spellingShingle TS Manufactures
M. F. F., Ab Rashid
Tiwari, Ashutosh
Hutabarat, Windo
Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
description Recently, interest in integrated assembly sequence planning (ASP) and assembly line balancing (ALB) began to pick up because of its numerous benefits, such as the larger search space that leads to better solution quality, reduced error rate in planning, and expedited product time-to-market. However, existing research is limited to the simple assembly problem that only runs one homogenous product. This paper therefore models and optimizes the integrated mixed-model ASP and ALB using Multi-objective Discrete Particle Swarm Optimization (MODPSO) concurrently. This is a new variant of the integrated assembly problem. The integrated mixed-model ASP and ALB is modeled using task-based joint precedence graph. In order to test the performance of MODPSO to optimize the integrated mixed-model ASP and ALB, an experiment using a set of 51 test problems with different difficulty levels was conducted. Besides that, MODPSO coefficient tuning was also conducted to identify the best setting so as to optimize the problem. The results from this experiment indicated that the MODPSO algorithm presents a significant improvement in term of solution quality toward Pareto optimal and demonstrates the ability to explore the extreme solutions in the mixed-model assembly optimization search space. The originality of this research is on the new variant of integrated ASP and ALB problem. This paper is the first published research to model and optimize the integrated ASP and ALB research for mixed-model assembly problem.
format Article
author M. F. F., Ab Rashid
Tiwari, Ashutosh
Hutabarat, Windo
author_facet M. F. F., Ab Rashid
Tiwari, Ashutosh
Hutabarat, Windo
author_sort M. F. F., Ab Rashid
title Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
title_short Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
title_full Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
title_fullStr Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
title_full_unstemmed Integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
title_sort integrated optimization of mixed-model assembly sequence planning and line balancing using multi-objective discrete particle swarm optimization
publisher Cambridge University Press
publishDate 2019
url http://umpir.ump.edu.my/id/eprint/25651/
http://umpir.ump.edu.my/id/eprint/25651/
http://umpir.ump.edu.my/id/eprint/25651/1/2019%20MM-ASPALB%20AIEDAM.pdf
first_indexed 2023-09-18T22:39:30Z
last_indexed 2023-09-18T22:39:30Z
_version_ 1777416820196638720

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