Emergency Material Scheduling For Dual Service Network With Supply And Demand Center

Emergency material scheduling is a very systematic logistics resource allocation problem.In emergency management activities,reasonable material scheduling can effectively reduce the adverse effects of unexpected disasters,and provide important material support for rapid rescue.However,judging from the heavy personal and economic losses caused by unexpected situations,the current level of human emergency management is still at a relatively backward level.Therefore,it is very important to constantly improve the emergency management mechanism and optimize the emergency material scheduling strategy.The dispatch of emergency materials is a complex process,including the selection of the rescue point,the distribution of emergency materials and the scheduling of vehicles.When natural disasters occur,the demand for materials and the extent of damage to the roads are usually unclear.Therefore,in the case of unclear information,the decision-makers use appropriate methods to develop an emergency scheduling scheme for the overall situation,to supply emergency materials in time and reduce unnecessary scheduling,which is the key problem to solve in the field of emergency material dispatch.Based on the above background,this paper researches on the optimal dispatching problem of emergency supplies in the dual service network of supply point demand point,establishes the corresponding mathematical model and designs the solving strategy,which provides practical guidance for emergency material scheduling.Firstly,this paper describes the research achievements of relevant scholars in the field of emergency supplies scheduling in recent years,analyzes the research status,identifies the research focus of this paper,and summarizes the modeling and solving methods of emergency material scheduling problem.Secondly,researching on certain emergency time –demand of single period emergency material scheduling,the problem is described and the mathematical model is constructed,and solves multi objective emergency supplies scheduling model of minimum emergency cost and shortest delay time with linear weighted sum method.Thirdly,researching on uncertain emergency time –demand of single period emergency material scheduling,we use interval number and triangular fuzzy number to express uncertainty of the material demand in demand point and the emergency time from supply point to demand point.We establish the mathematical model,transform the uncertain scheduling problem into a deterministic problem through mathematical theory,and verify the effectiveness of the model and algorithm with a case.Finally,on the basis of the first two chapters,the emergency material scheduling for multi-period working service network with dual demands is studied and formulated as a mixed integer programming model(MIP).Because of inefficient solving the mix integer programming model by conventional method,the MIP model must be improved.By introducing respectively two type parameters into the MIP model,reconstruction model with single preset incremental parameters(RM-SPIP)and reconstruction model with double preset incremental parameters(RM-DPIP)are presented.Further,piecewise methodology by updating preset control parameters(PM-PCP)is obtained.Computational results indicate that two reconstruction models by the proposed solution procedure can generate a better solution and show reasonable computing time.In this paper,we consider that each emergency period matches the best logistics resources as the starting point,and take the information characteristics of demand point and static and dynamic scheduling as the axis,and gradually study the emergency material scheduling,build a mathematical model for problem description and solve it.The results show that the proposed models and solution methods can effectively shorten the emergency time,reduce the emergency cost and improve the vehicle scheduling efficiency,providing a theoretical and practical reference for the rational scheduling of emergency materials.