Title: Metaheuristics for the Integrated Machine Allocation and Layout Problem

Authors: Juan R. Jaramillo, Alan R. McKendall

Addresses: Department of Business Administration, Albany State University, 504 College Drive, Albany, GA 31705, USA. ' Department of Industrial and Management Systems Engineering, West Virginia University, 325A Mineral Resources Building, Morgantown, WV 26505, USA

Abstract: The Integrated Machine Allocation and Layout Problem (IMALP) is the problem of assigning a set of machines (including machine replicas) to locations while assigning product flows to machines such that Material Handling Cost is minimised. A new mathematical formulation, a Tabu Search (TS) heuristic, and a Memetic Algorithm (MA) are presented for the IMALP. The algorithms were evaluated using a set of test problems available in the literature. TS and the MA obtained equal or better solutions for the dataset than previous techniques presented in the literature. More specifically, TS obtained better solutions in 47% of the instances, and MA improved the best known solution in 52.4% of the cases. As a result, MA out-performed TS with respect to solution quality and computation time.

Keywords: machine allocation; machine layout; IMALP; memetic algorithms; metaheuristics; multicommodity flow problem; quadratic assignment problem; Tabu search; product flows; materials handling cost.

DOI: 10.1504/IJOR.2010.029518

International Journal of Operational Research, 2010 Vol.7 No.1, pp.74 - 89

Published online: 30 Nov 2009 *

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