A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization

Ean, Kate Nee Goh and Jeng, Feng Chin and Wei, Ping Loh and Chea, Ling Tan (2014) A Constraint Programming-based Genetic Algorithm (CPGA) for Capacity Output Optimization. Journal of Industrial Engineering and Management, 7 (5). pp. 1222-1249. ISSN 2013-8423

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Abstract

Purpose: The manuscript presents an investigation into a constraint programming-based genetic algorithm for capacity output optimization in a back-end semiconductor manufacturing company. Design/methodology/approach: In the first stage, constraint programming defining the relationships between variables was formulated into the objective function. A genetic algorithm model was created in the second stage to optimize capacity output. Three demand scenarios were applied to test the robustness of the proposed algorithm. Findings: CPGA improved both the machine utilization and capacity output once the minimum requirements of a demand scenario were fulfilled. Capacity outputs of the three scenarios were improved by 157%, 7%, and 69%, respectively. Research limitations/implications: The work relates to aggregate planning of machine capacity in a single case study. The constraints and constructed scenarios were therefore industry-specific.

Item Type:	Article
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ1-1570 Mechanical engineering and machinery
Divisions:	Kampus Kejuruteraan (Engineering Campus) > Pusat Pengajian Kejuruteraan Mekanikal (School of Mechanical Engineering) > Article
Depositing User:	Mr Noorazilan Noordin
Date Deposited:	20 Dec 2017 01:42
Last Modified:	20 Dec 2017 01:42
URI:	http://eprints.usm.my/id/eprint/37999

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