The Emergency Vehicle Routing Problem with Uncertain Demand under Sustainability Environments

Jin Qin, Yong Ye, Bi-rong Cheng, Xiaobo Zhao and Linling Ni
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Jin Qin: School of Traffic and Transportation Engineering, Central South University, Changsha 410012, China
Yong Ye: School of Traffic and Transportation Engineering, Central South University, Changsha 410012, China
Bi-rong Cheng: School of Information Engineering, Wuyi University, Nanping 354300, China
Xiaobo Zhao: Guangzhou Port Company Ltd., Guangzhou 510100, China
Linling Ni: Dongfang College, Zhejiang University of Finance & Economics, Hangzhou 310000, China

Sustainability, 2017, vol. 9, issue 2, 1-24

Abstract: The reasonable utilization of limited resources is critical to realize the sustainable developments. In the initial 72-h crucial rescue period after the disaster, emergency supplies have always been insufficient and the demands in the affected area have always been uncertain. In order to improve timeliness, utilization and sustainability of emergency service, the allocation of the emergency supplies and the emergency vehicle routes should be determined simultaneously. Assuming the uncertain demands follow normal distribution, an optimization model for the emergency vehicle routing, by considering the insufficient supplies and the uncertain demands, is developed. The objective function is applied to minimize the total costs, including the penalty costs induced by more or less supplies than the actual demands at all demand points, as well as the constraints of the time windows and vehicle load capacity taken into account. In more details, a solution method for the model, based on the genetic algorithm, is proposed, which solves the problem in two stages. A numerical example is presented to demonstrate the efficiency and validity of the proposed model and algorithm.

Keywords: critical rescue period; vehicle routing; insufficient supplies; time windows; genetic algorithm (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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