Co-optimization Of Emergency Distribution Center Location Allocation Considering Uncertain Supply And Demand

Sudden disasters are hazardous and unpredictable,in which scientific emergency response is key to rescue.The efficiency of emergency relief depends on the reasonable planning of emergency logistics network and distribution of relief materials.With limited time and various uncertainties interfering decision making,delivering relief materials to disaster areas at the fastest speed while maximizing their needs is the primary task of emergency response in the early response stage.This thesis mainly focuses on the research shortage on joint decision-making in the preparation and initial post-disaster response stage of emergency management in China,which takes the three-layer logistics network of "supply point-logistics distribution center-demand point" as the research object,and conducts an in-depth discussion on cooptimization of emergency distribution center location allocation considering uncertain supply and demand.The thesis firstly outlines the basic theory of emergency management and classical algorithm of location-allocation problem.Then,a location-allocation cooptimization model of emergency logistics with objectives of shortest rescue time and maximum demand satisfaction rate of uncertain supply and demand at the early response stage is established.After that,considering the advantages of particle swarm algorithm and plant growth simulation algorithm,a hybrid optimization algorithm is designed to solve the location-allocation model.Finally,the proposed model and algorithm are applied to solve the scheduling scheme of emergency location-allocation case of epidemic prevention and control in Handan city.The results show that the number of emergency distribution centers plays a crucial role in the location allocation model.When three emergency distribution centers are set in Handan emergency logistics network,the total emergency rescue time reaches the shortest,the demand satisfaction rate is the highest,and the objective function gets the optimal solution.