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A robust optimization approach to dispatching technicians under stochastic service times

机译:在随机服务时间内调度技术人员的强大优化方法

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We consider the problem of dispatching technicians to service/repair geographically distributed equipment. This problem can be cast as a vehicle routing problem with time windows, where customers expect fast response and small delays. Estimates of the service time, however, can be subject to a significant amount of uncertainty due to misdiagnosis of the reason for failure or surprises during repair. It is therefore crucial to develop routes for the technicians that would be less sensitive to substantial deviations from estimated service times. In this paper we propose a robust optimization model for the vehicle routing problem with soft time windows and service time uncertainty and solve real-world instances with a branch and price method. We evaluate the efficiency of the approach through computational experiments on real industry routing data.
机译:我们考虑了派遣技术人员维修/修理地理上分散的设备的问题。可以将这个问题解释为带有时间窗的车辆路径问题,客户期望快速响应和小的延迟。但是,由于对维修过程中故障原因或意外原因的误诊,维修时间的估计可能会有很大的不确定性。因此,至关重要的是为技术人员开发对估计的服务时间的实质性偏差不太敏感的路线。在本文中,我们针对具有软时间窗和服务时间不确定性的车辆路径问题提出了一个鲁棒的优化模型,并通过分支和价格方法解决了实际情况。我们通过对实际行业路由数据进行计算实验来评估该方法的效率。

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