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Optimization of mixed-model assembly line balancing problem with resource constraints

M. M., Razali and M. F. F., Ab Rashid and M.R.A., Make (2017) Optimization of mixed-model assembly line balancing problem with resource constraints. In: Proceedings of Mechanical Engineering Research Day 2017. Centre for Advanced Research on Energy (CARe), pp. 115-117. ISBN 9789670257884

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Abstract

In this study, mixed-model assembly line balanuinfi problem is used to- analyze the performance of four evolutionary algorithms (E'As), namely particle swarm optimization (PSO), simulated annealing (SA), ant colony optimization (ACO) and genetic algorithm (GA). Three categories of test problem (small, medium, and large) is used ranging from 8 to 100 number of tasks. For computational experiment, MATLAB software is used in investigate the EAs performance to optimize the designated objective function. The results reveal that ACO performed hetter in lerm of solution quality of fitness function However, in term of processing time, PSO was the fastest followed by ACO. GA, and SA.

Item Type: Book Section
Subjects: T Technology > TJ Mechanical engineering and machinery
Faculty/Division: Faculty of Mechanical Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 26 Jul 2017 04:31
Last Modified: 25 Jan 2018 04:15
URI: http://umpir.ump.edu.my/id/eprint/18289
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