Abstract:

Takeout distribution optimization includes order allocation and route planning. Aiming at dynamic order and rider position change, with the goal of minimizing the overtime order proportion, average delivery time and average travel distance,a two-stage mathematical model is established based on the idea of pre-optimization and dynamic adjustment. In the pre-optimization stage, an improved variable neighborhood search algorithm is designed to obtain the initial distribution scheme. In the dynamic adjustment stage, a periodic optimization strategy is adopted to transform the problem into a virtual distribution center vehicle problem for solution. In each stage,different clustering methods are used to optimize the initial solution quality for faster solution. The effectiveness and feasibility of the proposed strategy and algorithm to solve the dynamic takeout distribution routing problem are verified and comparatively analzed. The research results not only deepen and expand PDVRP related theoretical research, but also provide a scientific takeout distribution optimization scheme for the takeout distribution platform.

Key words: takeout distribution, dynamic demand, order clustering, period optimization, improved VNS