关键词: 软时间窗, 同时集配货车辆路径, 粒子群算法, 变邻域下降搜索

Abstract: In order to solve the Vehicle Routing Problem with Simultaneous Pickup and Delivery（VRPSPD） with soft windows, a optimization model is developed for minimizing the total cost, which includes the vehicle dispatching cost, driving cost and penalty for time window. The hybrid particle swarm optimization algorithm is proposed to solve this problem, the algorithm is combined with variable neighborhood down search as the main body of the adaptive disturbance mechanism, using adaptive neighborhood strategy choice, and applying a variable number of cycles in each neighborhood search to improve the detection capability and search efficiency of the solution space. The Adaptive Perturbation Mechanism, which is based on the descending search of variable neighborhoods, adapts to the selection of neighborhood strategy and applies a variable number of cycles in each neighborhood search to improve the detection capability and search efficiency of the solution space. Numerical experiments show that the algorithm is feasible and effective.

Key words: soft time window, vehicle routing problem with simultaneous pickup and delivery, particle swarm optimization, variable neighborhood descent