Lean Logistics Path Optimization Based On Improved Ant Colony Algorithm

With the development of global economy and the intensification of enterprise's competition day by day, management of enterprise already vary gradually from original popular marketing stage with little variety and mass production to discrepant marketing stage which take with much variety and small quantity production as characteristic. The ones that manage to subdivide consumer colony and guided in time and feedback to enterprises management from market became main management strategy. Advanced and efficient logistics distribution can create higher economic benefits of enterprise and is the most important way to improve its competition capacity. However, there are many problems in logistics distribution of traditional Supply Chain Management, such as unreasonable inventory, slow response and the single processing needs. So, an advanced logistics distribution is needed. The idea that "while offering satisfying service to the customer, lowering waste to minimum extent" began to be noticed by people, it turns to be the goal of lean logistics as well, consequently, the study on lean logistics management has already become inevitable.In logistics, distribution is crucial and directly linked with the customers. Whereas, the optimization of vehicle planning of the distribution system is a key part of the whole system. By the optimization of vehicle planning, the enterprises can improve their nucleus competitiveness and achieve scientific process of logistics. The paper sets about from argumentation of logistics and lean thinking, and mainly studied on the Vehicle Routing Problem (VRP) in distribution system. With the comparison of VRP and the expanded problems about VRP, this paper establishes a model which matches with the optimization of routing to lean logistics. To solve this problem, this thesis proposes a new improved ant colony algorithm, which can overcome the shortcomings of traditional ant colony optimization algorithm (ACO), such as early convergence or stagnation in the process of combination. At last we realize the improved algorithm by MATLAB. The algorithm given in this paper can obtain an optimized solution effectively and has been proved to be a good scheme to solve VRP.