Optimization Of Vehicle Routing Problems Of Cold Chain Products With Simultaneous Pick-up And Delivery With Fuzzy Time Windows In B2C Model

In the e-commerce transactions of cold chain products,customers obtain limited information through online shopping.And if the delivery time is too long,customers'satisfaction with the goods and services purchased will decline.At the same time,because of the higher demand for the delivery process of cold-chain products,the whole process of distribution needs to maintain refrigeration,and customers' requirements are higher,including satisfaction on the service,arrival time of the delivery vehicle,the quality of products and return of products as soon as possible.Therefore,the route of cold-chain goods distribution vehicles should be planned reasonably in order to reduce the cost of distribution,achieve the minimum of distribution costs.Besides,the punctuality of distribution services should be improved so that customer' requirements of delivery and return can be met,and customer' satisfaction will be improved.This paper studies the problem which belongs to the vehicle routing problem with simultaneous delivery and pick-up.The current domestic and foreign scholars study on this problem mainly focuses on the simulated annealing algorithm,ant colony algorithm,and particle swarm optimization algorithm to make improvements to enhance the solving efficiency,and the time window introduced is classical time window.Besides,very few studies take cold chain logistics as a case study of such issues,and most don't consider the requirements of customer satisfaction or the ambiguity of time window.In order to solve the problem effectively,aiming at the feature of direct distribution service offered by enterprises in B2C and the particularity that the cold chain product is easy to be perishable,this paper defines the customers' satisfaction level and set up the corresponding time punishment cost function.A model of Vehicle Routing Problem with Simultaneous Pick-up and Delivery with Fuzzy Time Windows of cold chain products is developed,with the objective function of total cost,including the cost of selecting vehicles,the cost of transportation,the cost of cargo loss,the cost of cooling and the cost of punishment.The genetic algorithm is proposed,and the results of experiments indicate that:the developed model is effective and could obtain solutions meeting the characteristics of simultaneous pick-up and delivery and the time window constraints;the proposed algorithm,which could find high quality solutions with high computation efficiency and stable results in small error region,is a kind of efficient algorithm to solve this problem.