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Parallel solver for vehicle routing and pickup and delivery problems with time windows based on agent negotiation

机译:基于座席协商的带有时间窗的车辆路径,接送问题的并行求解器

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In this paper we present a parallel solver for the vehicle routing problem with time windows (VRPTW) and the pickup and delivery problem with time windows (PDPTW). The solver is based on parallel competition of particular solvers solving the given problem instance. The particular solvers are based on negotiation between a fleet of agents representing individual vehicles using a cost structure corresponding to the wellknown travel time savings insertion heuristic. The performance of the solver is assessed on the Homberger-Gehring and Li-Lim benchmark sets for the VRPTW and PDPTW case respectively. While both sets are widely used across the routing community, they were not addressed by previous agent-based studies. Thus the achieved average solution quality of 95% and 87% for the VRPTW and PDPTW cases represents a new best known result for these benchmark sets for agent-based approaches. An analysis of the solver's convergence, runtime and parameter sensitivity is provided within the experimental evaluation section, that has also not been provided by previous agent-based studies.
机译:在本文中,我们提出了一个带有时间窗(VRPTW)的车辆路径问题和带有时间窗(PDPTW)的收货和送货问题的并行求解器。求解器基于特定求解器对给定问题实例的并行竞争。特定的求解器基于使用对应于众所周知的旅行时间节省插入启发式的成本结构的代表各个车辆的代理团队之间的协商。分别根据VRPTW和PDPTW情况的Homberger-Gehring和Li-Lim基准集评估求解器的性能。虽然这两种方法都在路由社区中广泛使用,但以前基于代理的研究并未解决这两种问题。因此,对于VRPTW和PDPTW案例,达到的平均解决方案质量分别为95%和87%,代表了这些基于代理方法的基准集的新的最著名结果。实验评估部分提供了对求解程序的收敛性,运行时间和参数敏感性的分析,而以前基于代理的研究也未提供该分析。

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