The Open Cybernetics & Systemics Journal

2017, 11 : 24-35
Published online 2017 February 28. DOI: 10.2174/1874110X01711010024
Publisher ID: TOCSJ-11-24

RESEARCH ARTICLE
A Stochastic Distribution Center Location Model for Earthquake Relief Supplies Based on Monte Carlo Simulation

Zhong Tong , Qiuwen Zhang, * , Jianfeng Zhu , Xiaofei Liu and Fei Yan

* Address correspondence to this author at the School of Hydropower and Information Engineering, Huazhong University of Science and Technology. 1037 Luoyu Road, Wuhan, China; Tel: +86 15972970505; Email: qwzhang_hust@163.com

ABSTRACT

Distribution center links the relief suppliers and affected people, making it an indispensable part in the transportation network of earthquake relief supplies. Therefore, the location of distribution center for earthquake relief supplies has significant influence on transportation cost, operation efficiency and logistics performance, which are important in reducing loss of lives and property.

In this paper, we first give a review of general facility location models and find out the traditional model most suitable to distribution center location for earthquake relief supplies. Then the special characteristics of relief supplies distribution center are analyzed in detail and a stochastic location model is proposed. The model is based on traditional P-median facility location model and stochastic road damage degree is introduced into the model being treated as a stochastic variable to better fit to actual situation. Monte Carlo simulation method is adopted to simulate the stochastic variable representing actual stochastic road damage situation after earthquake disasters to solve the model. At last, an illustrative example of Wenchuan earthquake is given to show the optimization process of the proposed model and verify the feasibility of the new model. Furthermore, solution comparison between the proposed method and traditional method is made to show the benefits of the new method introduced in our paper.

Keywords:

Facility location, Earthquake relief supplies, Road damage, P-median model, Monte Carlo simulation.