Title: A multi-objective coincidence memetic algorithm for a mixed-model U-line sequencing problem

Authors: Parames Chutima, Noppon Kampirom

Addresses: Industrial Engineering, Chulalongkorn University, Bangkok 10330, Thailand. ' Industrial Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Abstract: A mixed-model U-line (MMUL) is a type of just-in-time (JIT) production systems where varieties of product models with similar product characteristics are assembled. Sequencing of product models to the MMUL is crucial to achieve the main benefits of JIT, i.e., set-up time reduction and levelled workload. In this paper, a new algorithm, namely combinatorial optimisation with coincidence plus memetic algorithm (COIN-MA), is proposed to find Pareto-optimal solutions for mixed-model sequencing problems. The performances of COIN-MA are compared with NSGA II, MNSGA II, and COIN against the metrics of convergence, spread, ratio of Pareto-optimal solutions, and CPU time. COIN-MA shows several outstanding characteristics against the others.

Keywords: mixed-model U-lines; just-in-time; JIT manufacturing; sequencing; non-dominated sorting genetic algorithms; NSGA II; MNSGA II; COIN; coincidence memetic algorithms; COIN-MA; multi-objective algorithms; production systems; product models; product characteristics; product assembly; set-up times; time reduction; levelled workloads; combinatorial optimisation; Pareto-optimal solutions; convergence; spread; ratios; central processing units; CPU time; advanced operations management.

DOI: 10.1504/IJAOM.2010.038338

International Journal of Advanced Operations Management, 2010 Vol.2 No.3/4, pp.201 - 248

Published online: 28 Jan 2011 *

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