Title: A memetic algorithm for the generalised machine layout problem

Authors: Juan R. Jaramillo; Alan McKendall

Addresses: Department of Business Management, Farmingdale State College, 2350 Broadhollow Road, Farmingdale, NY 11735, USA ' Department of Industrial and Management Systems Engineering, West Virginia University, 325A Mineral Resources Building, Morgantown, WV 26506, USA

Abstract: Designing efficient machine layouts is a key issue to ensure profitability in manufacturing environments. The major decisions in designing machine layouts are: the selection of machines (including machine replicas); the assigning of machines to the plant floor; the selection of production mix (i.e., determine the products to be produced); and the assigning of products to machines (i.e., determining the product flows). The generalised machine layout problem (GMALP) integrates these factors under a single problem. The contribution of this paper is the development of a memetic algorithm for the GMALP. The memetic algorithm takes advantage of the diversification strategies of the genetic algorithm combined with the intensification strategies of tabu search. Results obtained with the memetic algorithm compares favourably with the results presented in the literature.

Keywords: memetic algorithm; generalised machine layout problem; GMALP; machine layout problem; MLP; evolutionary algorithms; tabu search; TS.

DOI: 10.1504/IJOR.2018.096489

International Journal of Operational Research, 2018 Vol.33 No.4, pp.497 - 511

Received: 14 Oct 2015
Accepted: 26 Dec 2015
Published online: 05 Dec 2018 *

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