Mixed-Model U-Shaped Assembly Line Balancing Problems with Coincidence Memetic Algorithm

Abstract

Mixed-model U-shaped assembly line balancing problems (MMUALBP) is known to be NP-hard resulting in it being nearly impossible to obtain an optimal solution for practical problems with deterministic algorithms. This paper pre-sents a new evolutionary method called combinatorial optimisation with coincidence algorithm (COIN) being applied to Type I problems of MMUALBP in a just-in-time production system. Three objectives are simultaneously considered; minimum number workstations, minimum work relatedness, and minimum workload smoothness. The variances of COIN are also proposed, i.e. CNSGA II, and COIN-MA. COIN and its variances are tested against a well-known algo-rithm namely non-dominated sorting genetic algorithm II (NSGA II) and MNSGA II (a memetic version of NSGA II). Experimental results showed that COIN outperformed NSGA II. In addition, although COIN-MA uses a marginal CPU time than CNSGA II, its other performances are dominated.

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P. Chutima and P. Olanviwatchai, "Mixed-Model U-Shaped Assembly Line Balancing Problems with Coincidence Memetic Algorithm," Journal of Software Engineering and Applications, Vol. 3 No. 4, 2010, pp. 347-363. doi: 10.4236/jsea.2010.34040.

Conflicts of Interest

The authors declare no conflicts of interest.

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