Parallel Scatter Search Approach for the MinMax Regret Location Problem

Parallel Scatter Search Approach for the MinMax Regret Location Problem

Sarah Ibri (Hassiba Benbouali University, Chlef , Algeria), Mohammed EL Amin Cherabrab (Hassiba Benbouali University, Chlef, Algeria) and Nasreddine Abdoune (Hassiba Benbouali University, Chlef, Algeria)
Copyright: © 2018 |Pages: 17
DOI: 10.4018/IJAMC.2018040101

Abstract

In this paper we propose an efficient solving method based on a parallel scatter search algorithm that accelerates the search time to solve the minmax regret location problem. The algorithm was applied in the context of emergency management to locate emergency vehicles stations. A discrete event simulator was used to test the quality of the obtained solutions on the operational level. We compared the performance of the algorithm to an existing two stages method, and experiments show the efficiency of the proposed method in terms of quality of solution as well as the gain in computation time that could be obtained by parallelizing the proposed algorithm.
Article Preview

2. Literature Review

To deal with issues related to the fluctuation of the demand for facilities and other uncertainties of the systems' parameters, different kinds of models were proposed in the literature. We may distinguish the congestion based location models and the scenarios based models. We have to note that other classifications of location models under uncertainty exist (Laporte, Nickel, & Saldanha da Gama, 2015; Snyder, 2006).

Complete Article List

Search this Journal:
Reset
Open Access Articles: Forthcoming
Volume 10: 4 Issues (2019): Forthcoming, Available for Pre-Order
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2015)
Volume 5: 4 Issues (2014)
Volume 4: 4 Issues (2013)
Volume 3: 4 Issues (2012)
Volume 2: 4 Issues (2011)
Volume 1: 4 Issues (2010)
View Complete Journal Contents Listing