Study On Optimization And Algorithm Of Emergency Material Scheduling Model

Since the 21st century,with the rapid development of human society,the demand for nature has far exceeded its tolerable limit.Coupled with the continuous contradictions and conflicts among countries all over the world,various emergencies have emerged in endlessly and intensified,seriously affecting the harmony and stability of society and the normal life of citizens.In order to minimize the loss and impact of emergencies,the research heat of emergency material scheduling has been high.After the occurrence of emergencies,people often only pay attention to time and ignore the cost,fuzzy demand for materials and road damage.How to allocate materials quickly,efficiently and reasonably is related to the smooth progress of rescue work.This paper mainly aims at the above problems.In the case of uncertainty,considering the factors such as traffic cost and road damage,this paper adopts a variety of transportation modes for emergency material allocation.On this basis,the multi-objective particle swarm optimization algorithm and NSGAII algorithm are improved accordingly,and the overall comparative analysis of numerical examples is used to judge which algorithm is more optimized.The main work of this paper includes the following aspects:Firstly,this paper studies on the premise that the reserve of emergency materials is greater than or equal to the demand of disaster areas.On this basis,the balance between supply and demand is considered to avoid the problem of waste caused by oversupply.However,emergency material scheduling does not mean the pursuit of time and desperate,so it takes into account the factors of timeliness and cost.Considering the uncertain material demand,road damage,multiple transportation modes and other factors,an emergency material scheduling model with the goal of minimizing the total transportation cost and the total time for materials to reach the disaster site is constructed.Secondly,based on the standard multi-objective particle swarm optimization algorithm,a linear decreasing weight strategy is introduced,which can effectively solve the problems that the method is easy to fall into the local optimal solution and vibrate near the global optimal solution.Then it points out the defects of the traditional NSGAII algorithm,such as poor convergence,high computational complexity and poor distribution.A quantum local search strategy is proposed to replace the random search algorithm,which effectively improves the convergence performance of the algorithm.Finally,the program is solved by MATLAB.Firstly,the schemes of multi-objective particle swarm optimization algorithm before and after the improvement are compared and analyzed,and then the schemes of standard NSGAII algorithm and improved NSGAII algorithm are compared and analyzed.Finally,all schemes of all algorithms are summarized for overall analysis.It is found that the NSGAII algorithm with quantum local search strategy is far better than the other three algorithms in terms of average shortest material arrival time and average minimum transportation cost,and the optimization effect is very significant.This paper not only provides a theoretical basis for the research of emergency logistics department,but also provides a certain reference for the research of emergency logistics department.