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Particle swarm optimization algorithm for a vehicle routing problem with heterogeneous fleet, mixed backhauls, and time windows

机译:具有异构车队,混合回程和时间窗的车辆路径问题的粒子群优化算法

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摘要

Today, companies need to collect and to deliver goods from and to their depots and their customers. This problem is described as a Vehicle Routing Problem with Mixed Linehaul and Backhaul customers (VRPMB). The goods delivered from the depot to the customers can be alternated with the goods picked up. Other variants of VRP added to VRPMB are Heterogeneous fleet and Time Windows. This paper studies a complex VRP called HVRPMBTW which concerns a logistic/transport society, a problem rarely studied in literature. In this paper, we propose a Particle Swarm Optimization (PSO) with a local search. This approach has shown its effectiveness on several combinatorial problems. The adaptation of this approach to the problem studied is explained and tested on the benchmarks. The results are compared with our previous methods and they show that in several cases PSO improves the results.
机译:如今,公司需要从仓库和客户处收集和运送货物。此问题被描述为具有混合线路回程和回程客户(VRPMB)的车辆路由问题。从仓库交付给客户的货物可以与提取的货物交替使用。添加到VRPMB的VRP的其他变体是异构机群和Time Windows。本文研究了一个称为HVRPMBTW的复杂VRP,它涉及物流/运输社会,这是文献中很少研究的问题。在本文中,我们提出了带有局部搜索的粒子群优化(PSO)。这种方法已经证明了其在几个组合问题上的有效性。在基准测试中说明并测试了这种方法对所研究问题的适应性。将结果与我们以前的方法进行比较,结果表明在某些情况下PSO可以改善结果。

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