حالت توزیع ترمینال لجستیک و بهینه سازی مسیر بر اساس الگوریتم کلونی مورچه Logistics Terminal Distribution Mode and Path Optimization Based on Ant Colony Algorithm

1 Introduction With the development and progress of society, the society has entered the era of Internet, Tmall, Jingdong and other large B2C e-commerce platforms are gradually complete, Tmall November 11th and December 12th shopping festivals are rather hot. In the daily consumption process, people can feel convenience and benefits brought by online shopping whenever and wherever, and they trust more on the online shopping. Therefore, Chinese online shopping transaction has expanded rapidly. China network shopping market data released by iResearch showed that, in 2016, Chinese online shopping market transactions was 2.8 trillion yuan, an increase of 48.7%, equivalent to 10.7% of total retail sales of consumer goods, and annual line penetration exceeding 10% for the first time. In the first quarter of 2017, the scale of online shopping market in China was 757.410 billion yuan, an increase of 45.2% over the same period. In the second quarter, the scale of China’s online shopping market was 872.410 billion yuan, an increase of 39.6% over the same period. The proportion of it in the total retail sales of social consumer goods is 12.3%, and the permeability is further improved. In the context of the supply side reform, as the ‘‘last kilometer’’ of e-commerce, the logistics link needs to further improve the quality and level of service. The terminal distribution, as the ‘‘last mile’’ of logistics, only contacts by the end user, which is a key part of the logistics. How to send the purchased goods to consumers safely, quickly, and conveniently directly affects the satisfaction of consumers for the entire logistics and even the whole online shopping. As a result, it is necessary to do a good job in the whole logistics scheduling and improve the efficiency of logistics. At the same time, the logistics terminal link also needs to take the corresponding methods and measures to adapt to consumer requirements on the delivery mode and efficiency, so as to further enhance the consumer satisfaction for online shopping activities [1]. In the paper, we mainly study the logistics terminal distribution mode and path optimization, and combined with the application of ant colony algorithm in the TSP, analyse the basic principle and implementation process of ant colony algorithm. In addition, through reference to map and field research, we consider the route length and road conditions (slope and congestion) of the the regional distribution point, and collect and draw the geographic information surrounding area A. Moreover, some key parameters in ant colony algorithm in value are chosen, and with the collected information as a concrete example, MATLAB simulation is carried out for the logistics terminal distribution path optimization based on ant colony algorithm, and its scientific nature and feasibility are verified.