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A strategic oscillation simheuristic for the Time Capacitated Arc Routing Problem with stochastic demands

机译:随机需求的电容电弧路由问题的战略振荡态度

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The Time Capacitated Arc Routing Problem (TCARP) extends the classical Capacitated Arc Routing Problem by considering time-based capacities instead of traditional loading capacities. In the TCARP, the costs associated with traversing and servicing arcs, as well as the vehicle's capacity, are measured in time units. The increasing use of electric vehicles and unmanned aerial vehicles, which use batteries of limited duration, illustrates the importance of time-capacitated routing problems. In this paper, we consider the TCARP with stochastic demands, i.e.: the actual demands on each edge are random variables which specific values are only revealed once the vehicle traverses the arc. This variability affects the service times, which also become random variables. The main goal then is to find a routing plan that minimizes the expected total time required to service all customers. Since a maximum time capacity applies on each route, a penalty time-based cost arises whenever a route cannot be completed within that limit. In this paper, a strategic oscillation simheuristic algorithm is proposed to solve this stochastic problem. The performance of our algorithm is tested in a series of numerical experiments that extend the classical deterministic instances into stochastic ones.
机译:电容电弧路由问题(TCARP)通过考虑基于时间的容量而不是传统的装载能力来扩展经典电容电弧路由问题。在TCARP中,以时间为单位测量与遍历和维修弧相关的成本以及车辆的容量。越来越多地利用使用有限持续时间的电池的电动车和无人驾驶飞行器的使用说明了时间电容路由问题的重要性。在本文中,我们考虑了随机需求的TCARP,即:每个边缘对每个边缘的实际需求是随机变量,只有在车辆遍历弧时才揭示特定值的随机变量。这种可变性影响服务时间,这也成为随机变量。然后,主要目标是找到一个路由计划,最大限度地减少所有客户所需的预期总时间。由于在每条路线上适用最大时间容量,因此每当在该限制内无法完成路由时,会产生惩罚时间的成本。本文提出了一种战略振荡血管态算法来解决这个随机问题。我们的算法的性能在一系列数值实验中进行了测试,该数值实验将经典的确定性实例扩展到随机的数值实例中。

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