中文摘要：

文章针对软硬时间窗共存装卸一体化车辆路径问题（vehicleroutingproblemwithsimultaneousdeliv—eryandpickupundercoexistenceofsoftandhardtimewindows，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。

英文摘要：

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.