Optimization Research Of Vehicle Distribution Path For Fresh E-commerce In Intelligent Direct Delivery Mode

As a new mode of fresh product sales,fresh e-commerce is more and more recognized and welcomed by the market.While it is convenient for consumers to live,it also brings new challenges to the operation of enterprises.The efficiency and quality of "last kilometer" distribution is related to the survival and development of enterprises.Timely response,fast delivery time,high product freshness and integrity of enterprises will win the advantage in the fierce market competition.Therefore,in recent years,it has also been widely concerned by scholars.In fact,there are many forms of terminal distribution,different forms have different characteristics,and the actual operation process is also quite different,the current research mostly regards terminal distribution as a whole concept,and the pertinence is weak.Intelligent direct delivery is one of the ways of terminal distribution,which is widely used in large cities,especially in young white-collar workers,double-worker families and so on,through the establishment of intelligent terminals in the community and the operation of consumers themselves.This mode is convenient and fast,safe and efficient,good fresh-keeping effect and broad market prospect.This paper takes the fresh intelligent direct investment mode as the research object,starts from the two objectives of minimizing the enterprise cost and maximizing customer satisfaction,constructs the vehicle distribution path optimization model under the intelligent direct investment mode.And through the improved genetic algorithm to carry out numerical experiments,compared to prove the effectiveness of the method.The details are as follows:First of all,it points out the research background and significance of this paper,and qualitative analysis of fresh e-commerce operation mode,multi-objective decision-making problem,vehicle path planning problem and so on.Based on the analysis of relevant research at home and abroad,the research purpose,methods and ideas of this paper are obtained.Since then,the basic part of the theory introduces the logistics distribution of fresh e-commerce,multi-objective vehicle path planning and other related theories in detail,and thus leads to the concept of "intelligent direct investment mode ",and analyzes the definition,classification and distribution process of intelligent direct investment mode in detail,which provides theoretical help for the later research.Secondly,this paper constructs a vehicle path optimization model under the fresh intelligent direct investment mode.Combined with the unique characteristics of fresh intelligent direct investment mode,the constituent elements of customer satisfaction and enterprise distribution cost are introduced in detail,and the detailed calculation method is given.The model takes the enterprise distribution cost and customer satisfaction as the optimization goal at the same time,and subtly transforms the multi-objective problem into the single-objective problem by linear weighting method.In addition,we set certain assumptions and constraints on the model,which is of strong practical significance.Next,this paper expounds a genetic algorithm idea which combines sorting selection method with roulette method,and introduces in detail the operation process of improving the selection,crossover,mutation and termination of genetic algorithm,so that the improved genetic algorithm can not only guarantee the loss of good individuals,but also avoid falling into global optimum,and the operation efficiency is high.Finally,we design a numerical experiment in the intelligent direct-cast mode and use the improved genetic algorithm to solve it.Finally,we obtain the optimal distribution path considering the distribution cost and customer satisfaction.On this basis,the conclusions of this paper are also obtained,and the shortcomings are put forward.