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Mathematical Problems in Engineering
Volume 2017, Article ID 6710929, 15 pages
Research Article

Solving a Two-Stage Stochastic Capacitated Location-Allocation Problem with an Improved PSO in Emergency Logistics

College of Field Engineering, The PLA University of Science and Technology, Nanjing 210000, China

Correspondence should be addressed to Wanhong Zhu; moc.liamg@6102gnohnawuhz

Received 12 November 2016; Revised 12 March 2017; Accepted 23 March 2017; Published 31 May 2017

Academic Editor: Jorge Magalhaes-Mendes

Copyright © 2017 Ye Deng et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


A stochastic expected value model and its deterministic conversion are developed to formulate a two-stage stochastic capacitated location-allocation (LA) problem in emergency logistics; that is, the number and capacities of supply centers are both decision variables. To solve these models, an improved particle swarm optimization algorithm with the Gaussian cloud operator, the Restart strategy, and the adaptive parameter strategy is developed. The algorithm is integrated with the interior point method to solve the second-stage model. The numerical example proves the effectiveness and efficiency of the conversion method for the stochastic model and the proposed strategies that improve the algorithm.