Research articles
ScienceAsia (): 295-305 |doi:
10.2306/scienceasia1513-1874...295
Multi-objective sequencing problems of mixed-model assembly systems using memetic algorithms
Parames Chutima*, Penpak Pinkoompee
ABSTRACT: This paper investigates the performance of local searches embedded in memetic algorithms for solving multi-objective mixed-model assembly line sequencing problems that are common in a just-in-time production system. Two inversely related objectives, namely, setup times and production rate variation, are simultaneously considered. We use memetic algorithms which are a type of evolutionary algorithm using a local search algorithm to exercise exploitation. Simulation results demonstrate that memetic algorithms employed in conjunction with an appropriate local search outperform highly meta-heuristic algorithms such as Strength Pareto Evolutionary Algorithm 2 and Non-dominated Sorting Genetic Algorithm II in terms of ability to find Pareto-optimal solutions.
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| Department of Industrial Engineering, Faculty of Engineering, Chulalongkorn University, Phayathai Road, Bangkok 10330, Thailand |
* Corresponding author, E-mail: Parames.C@chula.ac.th
Received 2 Feb 2009, Accepted 30 Jun 2009
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