软硬时间窗共存装卸一体化车辆路径问题的混合离散粒子群优化算法

Hybrid discrete particle swarm optimization algorithm for vehicle routing problem with simultaneous delivery and pickup under coexistence of soft and hard time windows

文章针对软硬时间窗共存装卸一体化车辆路径问题(vehicle routing problem with simultaneous delivery and pickup under coexistence of soft and hard time windows,VRPSDPCSHTW)建立了包含车辆固定出行成本、运输成本和惩罚成本的数学模型,提出了一种混合离散粒子群优化算法。针对基本离散粒子群算法容易早熟收敛而陷入局部最优等问题,内嵌一种变邻域下降局域搜索方法,并在一定概率下执行以加强种群搜索能力,最后通过3个算例的仿真分析进行了算法验证。

In this paper, a general mathematical model of the vehicle routing problem with simultaneous delivery and pickup under coexistence of soft and hard time windows（VRPSDPCSHTW）, which con- tains fixed cost, travel cost and punished cost of vehicles, was established. And a hybrid discrete par- ticle swarm optimization algorithm was proposed. In order to solve the problems of premature conver- gence and easily falling into local minimum in the basic discrete particle swarm optimization algorithm, a simple variable neighborhood descent search algorithm as a local search procedure was embedded in the basic algorithm and was carried out under a certain probability. Finally, the performance of the proposed method was examined by three numerical cases.