An improved GRASP method for the multiple row equal facility layout problem

Abstract

As it is well documented in the literature, an effective facility layout design of a company significantly increases throughput, overall productivity, and efficiency. Symmetrically, a poor facility layout results in increased work-in process and manufacturing lead time. In this paper we focus on the Multiple Row Equal Facility Layout Problem (MREFLP) which consists in locating a given set of facilities in a layout where a maximum number of rows is fixed. We propose a Greedy Randomized Adaptive Search Procedure (GRASP), with an improved local search that relies on an efficient calculation of the objective function, and a probabilistic strategy to select those solutions that will be improved. We conduct a through preliminary experimentation to investigate the influence of the proposed strategies and to tune the corresponding search parameters. Finally, we compare our best variant with current state-of-the-art algorithms over a set of 552 diverse instances. Experimental results show that the proposed GRASP finds better results spending much less execution time.

Publication
Expert Systems with Applications
Nicolas Rodriguez Uribe
Nicolas Rodriguez Uribe
Phd in Artificial Intelligence
Alberto Herrán González
Alberto Herrán González
Associate Professor
J. Manuel Colmenar
J. Manuel Colmenar
Associate Professor

My research interests are focused on metaheuristics applied to optimization problems. I have worked on different combinatorial optimization problems applying trajectorial algorithms such us GRASP or VNS. Besides, I am very interested in applications of Grammatical Evolution, specifically in model and prediction domain, as alternative to machine learning approaches.

Abraham Duarte
Abraham Duarte
Full Professor

Abraham Duarte is Full Professor in the Computer Science Department at the Rey Juan Carlos University (Madrid, Spain). He has done extensive research in the interface between computer science, artificial intelligence, and operations research to develop solution methods based on Computational Intelligence (metaheuristics) for practical problems in operations-management areas such as logistics and supply chains, telecommunications, decision-making under uncertainty and optimization of simulated systems.