Research On Vehicle Routing Problem With Fuzzy Demand And Time Window

With the globalization of the world economy and the development of e-commerce,the role of logistics in economic activities is becoming more and more obvious.As an important material basis of today's economic activities,the core driving force of the development of e-commerce era is the development of logistics.The specific mode of logistics even determines the specific node of economic operation.The development of logistics has provided the possibility to meet the needs of all over the world,so it has been paid more and more attention by enterprises.Distribution,as the key link of modern logistics,is an important link between enterprises and enterprises,enterprises and consumers.Therefore,reasonable vehicle routing planning can not only improve the benefits of enterprises,reduce the operating costs of enterprises,but also speed up the response to customer needs and improve customer satisfaction.On the one hand,in the actual logistics distribution,there are often some information that can not be known beforehand,and it is difficult to deal with it in a random way.On the other hand,some related literatures have studied VRP with multi-fuzzy variables,but VRP with customer service time window and customer demand fuzzification has not been effectively solved.Therefore,it is particularly necessary to study the vehicle routing problem with fuzzy demand and time windows.Firstly,by reading a large number of literatures,this paper summarizes the research on vehicle routing problem with time windows,multi-objective vehicle routing problem,vehicle routing problem with fuzzy demand,vehicle routing problem with fuzzy time windows and multi-fuzzy variable vehicle routing problem.The direction of research is discussed.Secondly,this paper systematically summarizes the definition,involved elements,types and solving algoritlun of vehicle routing problem,expounds the basic theory of establishing the model in this paper,that is,the credibility measure theory,and expounds the concept,solving method of multi-objective optimization problem and the genetic algorithm used in this paper.Then,the problem studied in this paper is described in mathematical language,and a fuzzy chance programming model is established to solve the problem.Finally,a hybrid genetic algorithm combining genetic algorithm with local search algorithm is designed to calculate the problem in this paper.In summary,aiming at the vehicle routing problem with fuzzy demand and time window,a multi-objective fuzzy chance constrained model based on credibility measure theory is constructed to minimize the total driving distance,vehicle usage and average customer satisfaction.On the basis of introducing local optimization algorithl and rolling table rule,a hybrid genetic algorithm suitable for solving multi-objective vehicle routing problem is designed.The VRPTW standard example shows that the algorithm can effectively solve the vehicle routing problem with time windows and the rationality of the model.At the same time,it shows the influence of the preference value of decision makers on the decision objectives.The research results can provide a way of thinking for solving vehicle routing problem with fuzzy demand and time window,and also provide guidance for actual distribution routing planning.