Rearch On Emergency Materials Distribution Based On Uncertainty Theory

In the emergency rescue,the delivery of emergency materials is one of the most important tasks.The timely delivery of emergency materials to the demand points for supplies can reduce the further loss of life and property caused by delays in rescue work after an emergency.Due to the uncertainty and urgency of emergencies,some of the key input parameters are invalid or missing,we need to ask expert based on their experience and comprehensive consideration to estimate those data,such as the transportation time and the amount of demand materials,and etc.Based on uncertainty theory,this study considers the estimated parameters as the uncertain variables as the input parameters of the models to solve the emergency material distribution problem.The main innovation points are:(1)A single rescue center of the emergency material distribution model is established.The uncertain variables are introduced to describe the data parameters missing in the allocation of emergency materials distribution and estimated by experts,such as the parameters of vehicle transportation time and material demand,etc.,and setup the emergency material distribution model with the minimized sum of transportation time as the objective function,vehicle capacity as the constraint.According the uncertainty theory,the equivalent model is deduced.A new hybrid intelligent algorithm(Genetic Algorithm with Cellular automata,CGA)is developed to solve the model.The numerical example is given to illustrate the application of the model and to verify the validity and robustness of the CGA algorithm(2)In view of the constraint of vehicle space,a three-dimensional loading strategy is proposed and a programming model of emergency material distribution under single rescue center considering three-dimensional packing is established.Due to the different types of emergency materials,in order to facilitate loading and unloading,emergency materials in vehicles are in need of classification placed.According the different length of each kind of materials,the loading strategy is put forward according to type of materials.With comparason of the height,length and width of the pile heap to the height,length and width of vehicle,it avoids the occurrence of vehicle space does not meet the demanded materials placed in the vehicle routing decision.Since the constructed model is a mixed integer programming model,an Improved Genetic Algorithm with Cellular automata(ICGA)is developed based on CGA,and ICGA is used to solve the new established model.The numerical example illustrates the importance of considering three-dimensional packing and verifies the robustness and validity of the ICGA algorithm(3)In the case of insufficient transportation capacity or materials stock limitation of single rescue center,this study gradually builds the multi-rescue center emergency material delivery planning models without and with taking vehicle space into account.By introducing uncertain variables,based on the uncertainty theory,the equivalent models of the model under uncertainty normal distribution without considering vehicle space limitation and a model under uncertainty zigzag distribution with considering the vehicle space limitation are deduced.The capacity in multiple rescue centers unified all vehicles in number indexing,to solve the problem of insufficient capacity of a single rescue center.According the stock of emergency materials,the unification of distribution of vehicles in multi-centers is used to address the problem of lack of inventory of a single rescue center.The ICGA algorithm is used to solve the models.Numerical examples are given to show that multiple centers are transported more efficiently than single rescue centers and the robustness and validity of the ICGA algorithm are verified as well.