An application of particle swarm optimisation with negative knowledge on multi-objective U-shaped assembly line worker allocation problems

Abstract

Multi-objective U-shaped manually operated assembly line worker allocation problems with symmetrical and rectangular layouts are addressed in this paper. The problems are optimised in a hierarchical manner. The primary objective is to minimise the number of workers and the second objective comprises two conflicting sub-objectives including the deviation of operation times of workers and the walking time which are minimised simultaneously. Mathematical formulation of the problems is presented. Since the problems are classified in the non-deterministic polynomial time hard type, a novel evolutionary algorithm, namely particle swarm optimisation with negative knowledge (PSONK), is proposed as a solution technique. The performance of PSONK is compared with several well-known algorithms, i.e. non-dominated sorting genetic algorithm-II, memetic algorithm (MA) and discrete particle swarm optimisation. PSONK and MA tend to give indifferent performance but they outperform the others. However, PSONK can reach final solutions much faster than the others, especially MA. Copyright © 2013 Inderscience Enterprises Ltd.