Vehicle Scheduling Problem Of Emergency Logistics Distribution Based On GA-ACO

Natural disasters and other emergencies occur frequently in our country, it requires a large amount of materials to deal with emergency supplies. Once the preparation of emergency material completed, how the emergency materials will effectively and quickly be transferred to the disaster needs place, which has became the focus of attention. In this case, to carry out emergency supplies scheduling, fast and promptly sent to the crucial place of disaster needs, and the emergency vehicle scheduling is the key part of disaster prevention and mitigation. Therefore, the research on emergency logistics distribution vehicle scheduling problem for improving the capacity, reduce the scope of the disaster, and minimize the loss of life and property has great realistic significance for emergency response.Firstly, this paper analyzes the research status of emergency vehicle scheduling of logistics distribution at home and abroad and existing problems in the research, and discusses the related theory of emergency logistics and vehicle scheduling problem. Secondly, combined with the characteristics of emergency logistics, emergency logistics distribution considering the timeliness, the weak economy, the condition of the road, a multi-objective vehicle scheduling model of emergency supplies with the objectives of the shortest emergency time and the least costing is established. Thirdly, this paper summarizes the advantages and disadvantages of the basic principle and algorithm of genetic algorithm and ant colony algorithm, and gives the design idea and basic steps of genetic ant colony algorithm. Finally, according to empirical background of data selection, on the basis of the algorithm design and parameter selection of vehicle scheduling, and a calculation is made to validate the feasibility and effectiveness of the model and the algorithm, and puts forward some countermeasures and suggestions to improve the ability of logistics distribution efficiency.