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首页> 外文期刊>Journal of Computers >A Hybrid Particle Swarm Optimization Algorithm for Multi-Objective Pickup and Delivery Problem with Time Windows
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A Hybrid Particle Swarm Optimization Algorithm for Multi-Objective Pickup and Delivery Problem with Time Windows

机译：具有时间窗口的多目标拾取和交付问题的混合粒子群优化算法

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—This paper studies the multi-objective pickup and delivery problem with time windows (PDPTW), in which a fleet of homogeneous vehicles with the same capacities located in a depot serve a collection of given transportation requests. Each request is composed of a pickup location, a delivery location and a given load. The PDPTW is to determine a vehicle scheduling strategy with the objectives of minimizing the number of vehicles utilized, the total travel distances and the total waiting times. A mixed integer programming model is built to formulate this multiobjective PDPTW. Then a novel hybrid particle swarm optimization (HPSO) is proposed to solve this problem. This algorithm adds particles neighbor information to diversify the particle swarm and use the variable neighborhood search (VNS) to enhance the convergence speed. Finally, some numerical experiments based on existing benchmark instances are given to show the effectiveness and feasibility of the algorithm.
机译：- 这篇论文研究了时间窗口（PDPTW）的多目标拾取和交付问题，其中一支具有相同容量的均匀车队，位于仓库中，提供了给定的运输请求的集合。每个请求由拾取位置，传送位置和给定负载组成。 PDPTW是确定车辆调度策略，其目的是最小化所使用的车辆数量，总行程距离和总等待时间。构建混合整数编程模型以制定此多目标PDPTW。然后提出了一种新的混合粒子群优化（HPSO）来解决这个问题。该算法添加了粒子邻居信息以使粒子群化多样化，并使用变量邻域搜索（VNS）来增强收敛速度。最后，给出了基于现有基准实例的一些数值实验，以显示算法的有效性和可行性。

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