Research On Vehicle Routing Problem Of Emergency Logistics Based On Genetic Algorithm

Nature disaster happened more frequently in recent years, causing massive damage tothe economic and people’s life. Hence VRP(Vehicle Routing Problem) of Emergency Logisticwhich is the vital link of post-disaster emergency rescue has been paid more attention. For themoment, the research on VRP of Emergency Logistic has been focused on optimization goalas minimum rescue time or rescue cost, the optimization goal based on the overall efficiencyhas not been discussed yet. As one of the major algorithm to solve the VRP, GA(GeneticAlgorithm) has its own limits, such as premature, overtime on calculating, algorithmperformance highly affected by genetic operator. The quality of the algorithm design isexpected to be improved.The primary goal of this research was to built mathematics model for VRP ofEmergency Logistics, and to apply GA to solve the model. The main research contents asfollowed:(1)summarized the major factors need to be considered in VRP of EmergencyLogistics, built optimization system of VRP of Emergency Logistics, and then built themathematics model for VRP of Emergency Logistics;(2)designed the adaption GA solving themathematics model for VRP of Emergency Logistics, which contains encoding and decodingchromosomes, select operator, adaptive cross operator and adaptive mutation operator;(3)Thedesigned algorithm was implemented in MATLAB7.1software to solve the VRP ofEmergency Logistic in an example, testing the validity of algorithm and analyzing algorithmperformance.Example Analyses in this research showed:(1)through the designed adaption GA, themathematics model for VRP of Emergency Logistics can be solved, confirming the validityboth of the model and the algorithm;(2)the "premature convergence" was not found duringthe process of solving the model with adaption GA;(3)through the comparative analysis ofexperimental data, the optimal solution quality of adaption GA was high than that of standardGA, and solving time of adaption GA was less than that of standard GA, which proved that the performance of adaption GA was better than that of standard GA.The proposal of mathematics model for VRP of Emergency Logistics in this thesis wasto benefit for resource reasonable configuration optimization of relief goods, labour powerand vehicle during Emergency Logistics. Meanwhile, the adaption GA designed in this thesiscan respond quickly and effectively to solve VRP of Emergency Logistics, making the bestdecision in time in order to ensure the safety of life and property in disaster-hit areas.