Research On Two Types Of Vehicle Routing Problem Based On Online Shopping Environment

With the rapid popularization of Internet technology and intelligent mobile phone, new opportunities have arisen for e-commerce’s high-speed development. Shopping online has gradually become an important means of people’s consumption. Logistics as the offline delivery’s necessary part of online shopping, plays an important role in the whole electronic trading. Logistics service with high quality is not only the important guarantee for earning of enterprise but also expectation of customers. Through efficient and accurate logistics delivery, it is not only improves the customer’s satisfaction with the degree of logistics service providers, but also enhances the customer loyalty to the e-commerce enterprise. As a result, e-commerce enterprises will get more market share and gain more profits.Due to the fierce competition in the online market, other than giving lower price to gain more users, e-commerce enterprises also consider to improve services of logistics delivery as another important means. Just under such a background, diversified logistic services appeared. Unsatisfied with spotty quality of many third party logistics service providers, a small number of e-commerce enterprise has set up its own self-run logistics distribution system and delivered most parcels by its own. In ensuring their online logistics service level and at the same time, they have become imitate benchmark for the most logistics enterprises. In fact, most of the e-commerce enterprises also choose the third party logistics providers to accomplish distribution tasks. Yet, during the delivery, sudden diverse changes of customers or cancel the order may happen, which would lead to failure of achievement of planned vehicle routing, and it would result to great loss of money.According to the current e-commerce logistics distribution background, two types of vehicle routing problem for online shopping environment is researched in this paper. The first kind is analyzing logistics distribution mode of enterprises with self-run logistics business. Based on the research for the cost of self-run logistics and the-third-party logistics respectively, we established the model of vehicle routing based on the third party. In this model, we considerd the improved genetic algorithm with population expansion mechanism to solved the problem. At last, its expriment data showed the algorithm was excellent. The second kind is researching the return policy in the online shopping. Using dynamic management method to analyze changes of receiving parcel during the delivery or cancel the order, we established a mathematical model on the purpose of optimizing the sum of minimum fluctuation for the customers service time, vehicle miles of travle, and cost spend. By using nested segmentation method to solve this model, test results proved the algorithm effect is fine. Through analyzing temporary refuse to receive or demand of pickup, we transferred it to pickup and delivery at the same time problem and set up a model. In consideration of many restraints of this question, we promoted genetic algorithm with maximum numerical chromosome encoding. And, experiments data proved it’s effective and feasible.