ThaiScience
ThaiScience
ENGINEERING JOURNAL CHIANG MAI UNIVERSITY
Volume 25, No. 02, Month AUGUST, Year 2018, Pages 67 - 78
Multi-objective sequencing on mixed-model parallel assembly lines with biogeography-based optimization
Thassanee Thongjun and Parames Chutima
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Multi-objective sequencing on mixed-model parallel assembly lines is known as an NP-hard problem. Hence, to optimize this problem, heuristic approaches need to be developed. In this research, a Biogeography-Based Optimization (BBO) algorithm is adapted to optimize three objectives simultaneously, which are minimum variance of production rates, minimum utility work, and minimum setup times. The performance of BBO is compared with the well-known algorithm, Nondominated Sorting Genetic Algorithms II (NSGA-II). The experimental results show that BBO outperforms NSGA-II in terms of convergence, ratios of non-dominated solutions and CPU time. In contrast, it is found that the spread metric of NSGA-II is a marginally better than that to BBO.
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Published by : Faculty of Engineering Chiang Mai University
Contributions welcome at : http://researchs.eng.cmu.ac.th/?name=journal
