An imperialist competitive algorithm for multi-objective U-type assembly line design |
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| Institution: | 1. Department of Industrial Engineering, Industrial and Mechanical Faculty, Islamic Azad University-Qazvin Branch, Qazvin, Iran;2. Department of Industrial Management, Management and Accounting Faculty, Shahid Beheshti University, Tehran, G.C., Iran;3. Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran;1. Virtual Plants, INRIA Sophia-antipolis, France;2. CIRAD/UMR AGAP, Avenue Agropolis, TA 40/02, 34398Montpellier, France;3. Parietal project-team, INRIA Saclay-île de France, France;4. CEA/Neurospin bât 145, 91191 Gif-Sur-Yvette, France;5. Simula Research Laboratory, P.O. Box 134 NO-1325 Lysaker, Norway;6. Department of Informatics, University of Oslo, P.O. Box 1080 Blinder, NO-0316, Norway;1. College of Engineering, Mathematics and Physical Sciences, North Park Road, University of Exeter, Exeter EX4 4QF, England, UK;2. Department of Industrial Engineering, Balikesir University, Cagis Campus, Balikesir, Turkey;3. State Key Laboratory on Mechanical Transmission, Chongqing University, Chongqing 400044, China;1. College of Engineering, Mathematics and Physical Sciences, North Park Road, University of Exeter, EX4 4QF Exeter, England, United Kingdom;2. Department of Industrial Engineering, Balikesir University, Cagis Campus, 10145 Balikesir, Turkey;3. State Key Laboratory on Mechanical Transmission, Chongqing University, Chongqing 400044, China |
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| Abstract: | Many assembly lines are now being designed as U-type assembly lines rather than straight lines because of the pressure of the just-in-time (JIT) manufacturing concept. Since any type of an assembly line balancing problem is known to be NP-hard, there has been a growing tendency toward using evolutionary algorithms to solve such a hard problem. This paper proposes a new population-based evolutionary algorithm, namely imperialist competitive algorithm (ICA) inspired by the process of socio-political evolution, to address the multi-objective U-type assembly line balancing problem (UALBP). Two considered objectives are to minimize the line efficiency and minimize the variation of workload. Furthermore, the Taguchi design is applied to tune the effective parameters of the proposed ICA. To demonstrate the efficiency of the proposed algorithm, the associated results are compared against an efficient genetic algorithm (GA) in the literature over a large group of benchmarks taken from the literature. The computational results show that the proposed ICA outperforms GA. |
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