Nonlinear Continuous Consumption Of Large-Scale Emergency Material Dispatching Problem

In recent years, various natural disasters occurred in our country, especially the large-scale natural disasters occurred frequently, which caused great casualties and economic losses. In order to ensure the emergency rescue work efficiently and orderly, The Chinese Government formulated and issued The National Emergency Preplans for Natural Disaster Relief. According to the harm of natural disasters, the government and relevant functional departments take corresponding emergency rescue measures. Emergency material is the material basis for the emergency rescue. In order to ensure the smooth implementation of emergency rescue, the government and relevant functional departments must quickly make effective and reasonable emergency material dispatching scheme, which will disperse the emergency material of the disaster sites and meet the demand of the disaster sites of the material, only in this way can maximize the effect of emergency rescue. But at the moment loss still account for 15% to 20%, which caused by the inefficient emergency material dispatching decision system damages. Efficient and reasonable emergency material dispatching scheme can not only effectively reduce the cost of emergency material dispatching, but also can improve the disaster sites'satisfaction. Therefore, the research on emergency material dispatching problem has important practical value and scientific significance.Multiple emergency material dispatching problem often has restrict the goal of each other, and is a typical multi-objective optimization problem. Meanwhile the traditional method to solve the problem of multi-objective optimization is difficult to converge to the Pareto optimal solution set, therefore the perspective of multi-objective optimization model and algorithm for emergency material dispatching problem are studied. This article main research content is as follows:In view of material competition and high cost problems in the nonlinear continuous consumption emergency material dispatching, firstly, the demand urgent degree was confirmed by using the improved grey relational method based on combination weighting, which was used to design the disaster place satisfaction coefficient and lack of material loss coefficient; secondly, a disaster sites, multi-rescue points, multi-material, multi-period and multi-objective emergency material dispatching model was established, which regarded the minimize total dispatching cost and maximize the disaster sites'satisfaction as optimization target. In the light of the characteristics of the multi-objective optimization model, a hybrid multi-objective particle swarm optimization algorithm that combined with improved particle swarm optimization algorithm and the local search algorithm based on the Hill Climbing with Sidestep(HCS) without using gradient information(IMOPSO_HCS) was used to solve the multi-objective problem, whitch was based on Pareto-dominance solutions. The algorithm didn't need to introduce bias in the solving process. It considerated the targets equally in the model, finally obtained a set of Pareto optimal solution set, and the selection of the different emergency material dispatching scheme depended on the actual demand of emergency material dispatching. In view of the two types typical satisfaction curve type of emergency materials, the numerical examples verified the rationality of the model and the efficiency of the algorithm. Simulation result indicates that the model and algorithm coordinate the disaster sites'satisfaction and emergency material dispatching cost, while getting higher the disaster sites'satisfaction and lower emergency material dispatching cost.