A Multi-objective Stochastic Planning Model For Emergency Logistics In Uncertain Environments

In recent years,public health crises have erupted worldwide due to globalization,notably the novel coronavirus(COVID-19)outbreak that has had detrimental impacts on social,environmental,and economic aspects,posing a serious threat to lives and property.Emergency logistics plays a crucial role in protecting people’s lives and property through effective emergency material rescue.However,shortages of emergency resources during the early stages of the epidemic could not meet the needs of all affected areas simultaneously.Therefore,this paper aims to efficiently and reasonably distribute emergency materials to affected areas based on differences in the epidemic situation,achieve the maximization of the value of emergency materials,and improve the timeliness and economy of distribution.To accomplish this,the paper comprehensively considers the characteristics of emergency materials under the epidemic background and the construction principles of the evaluation index system.It analyzes the influencing factors of the priority of emergency material distribution for each demand point and constructs a relevant index evaluation system.The paper proposes an AHP-CRITIC improvement method to determine the comprehensive weights of various indicators,obtains quantified and weighted priority evaluation indicators,and determines the distribution order of each affected area using the grey correlation TOPSIS priority evaluation method based on prospect theory.The priority is then introduced into the subsequent emergency material scheduling model,maximizing the utility value of emergency materials.As the epidemic has a long duration and a wide range of effects,the paper considers a multi-period and multi-objective stochastic programming model for emergency material scheduling.The model aims to minimize transportation time,total scheduling costs,and the unsatisfied demand rate of weighted priorities for affected areas.This paper constructs a stochastic emergency material scheduling optimization model under random demand and considers the economy and timeliness of scheduling while pursuing the maximization of the utility value of emergency materials.To solve the scheduling model,the paper uses the slime mold optimization multi-objective ant algorithm.Finally,the paper conducts a case study with 13 administrative districts in Wuhan,Hubei Province,affected by the epidemic as material demand points.The grey correlation TOPSIS method based on prospect theory is used to calculate the distribution priority of each demand point,and the results are compared with those obtained by the TOPSIS method and the entropy weight TOPSIS method.On this basis,the paper uses the slime mold optimization multi-objective ant algorithm to solve the multi-objective stochastic programming scheduling model and compares the results with those obtained by the slime mold algorithm and the ant algorithm to verify the model and method’s effectiveness.