Evaluation Of Equity And Modeling Of Location-Allocation Problem In Disaster Relief

In recent years,China has witnessed frequent occurrence of various large-scale natural disasters,including the wenchuan earthquake in 2008,the typhoon rammasun in 2014,and the flood in the Yangtze river basin in 2016.While natural disasters have caused huge losses to the country and society,they have also brought great suffering to the victims.Emergency logistics has turned mature over a decade of development.Hundreds of studies provided a great number of strategies and solutions to improve relief operations from both effectiveness and efficiency perspectives.Along with the deepened study,expectations have also increased.Besides effectiveness and efficiency,there is a call for more attention to equity.As one of three performance principles,ignoring equity not only has negative effect on the performance of a relief operation,but also puts the whole operation at stake.Therefore,studying equity in emergency relief has both academic and practical significance.The paper has studied the specific characteristics of equity in the humanitarian context.This paper suggests the use of inequity aversion and proposes graded pairs comparison(GPC)to collect preference intensity data.By collecting first-hand data from individuals with and without disaster experience,this paper studies equity from the perspective of inequity degree,direction of inequity and supply degree.The analysis generates several observations and shows differences in inequity aversion between individuals with and without disaster experience.The study also demonstrates that the inequity aversion functions(IAFs)can be derived and expressed as a modified reciprocal function in which inequity degree and supply degree are considered.In order to improve the performance of emergency rescue operations,it is important not only to build appropriate objective function,but also to integrate and optimize the whole rescue operation.In the early stage of large-scale disasters,emergency supplies cannot meet all the needs in time,and the beneficiaries suffer from the lack of goods and services.A numerical rating scale(NRS)is designed to construct a suffering function in order to describe the suffering perception cost of the beneficiaries.In this paper,beneficiaries’perception is incorporated into the decision-making of total emergency cost.Considering evacuation and resettlement of victims,location of temporary shelters and distribution of materials,an integrated optimization model is proposed,with the minimum total social cost(the sum of logistics cost and psychological cost of suffering)as the objective of emergency rescue.The classical mixed integer programming method and improved genetic algorithm are designed to solve the model in the scenario of typhoon Wilmson in Hainan.The numerical results show that the model and algorithm can effectively solve the problem of shelter location and material allocation considering human suffering.It reveals that with the increase of disaster scale and the decrease of evacuation time,the genetic algorithm outperforms the classical method.