Robust Optimization Of Vehicle Routing For Emergency Material Transport

In the past decade,various emergency events have occurred frequently,posing a threat to social development and people’s lives both domestically and abroad,for instance,the global COVID-19 and the Ebola event in Congo in 2018,etc.Such outbreaks need to be prevented and controlled in a timely manner,otherwise the harm will further expand and evolve.For instance,a large number of emergency materials are urgently needed in infected areas with different urgency after the outbreak of infectious diseases,which requires timely arrangement of vehicles to transport materials to the demand points,so choosing the scientific and reasonable transportation routes has become an important issue that decision makers need to solve.Therefore,this paper focuses on the path planning problem of emergency material transportation vehicles in the context of such emergencies as infectious diseases,and the robust optimization theory is introduced,the paper is subdivided into the following sub-problems.(1)Demand analysis and calculation of emergency materials.First,when the demand is determined,the nominal demand is estimated by combining the triangular fuzzy number theory and PERT method for defuzzification of the uncertain variables.Then,in the case of uncertain demand,the Box uncertainty set is introduced to portray the uncertain demand in various areas in order to estimate the demand box set.Finally,improved grey relation analysis(I-GRA)based on combined weights to estimate the unknown data of service urgency in each place for the problem of material competition in non-linear continuous consumption emergency material transportation.(2)Vehicle routing of emergency materials transportation under determinate demand.A two-layer structure system for vehicle distributing emergency supplies was constructed and which was mathematically abstracted using appropriate parameters,variables and expressions.Then,a mathematical model with the objective of minimizing the vehicle travel time and time penalty cost in the network system was established with time as the limiting condition,and the urgency at each demand point was introduced and analyzed with the example of the epidemic in Hubei Province.(3)Vehicle routing of emergency materials transportation under uncertain demand.First,multi-vehicle transportation and multi-objective robust optimization of vehicle routing with single distribution center: Combined with the robustness of the solution,the soft time window restriction is introduced,and the cost of vehicle distribution is considered comprehensively,then,a robust model of the vehicle path for the emergency material transportation is established,and a case study is introduced for analysis.Then,multi-vehicle transportation and multiobjective robust optimization of vehicle routing with multi-distribution center: The "robustness" factor is introduced to study how to plan the emergency material transportation vehicle routes with the most robust and least cost under the conditions of using the least number of vehicles,the shortest travel time and the least transportation cost.In this paper,an example analysis is given for each sub-problem.The results show that the nonlinear models constructed and the improved genetic algorithm designed in this paper can find the route scheme of emergency material transportation vehicles with different robustness,which provides some reference for decision makers to find a timely and economical emergency material transportation vehicles route solution with high service satisfaction and robustness.