{"title":"有限容量的叫车问题","authors":"M. Charikar, B. Raghavachari","doi":"10.1109/SFCS.1998.743496","DOIUrl":null,"url":null,"abstract":"We give the first non-trivial approximation algorithm for the Capacitated Dial-a-Ride problem: given a collection of objects located at points in a metric space, a specified destination point for each object, and a vehicle with a capacity of at most k objects, the goal is to compute a shortest tour for the vehicle in which all objects can be delivered to their destinations while ensuring that the vehicle carries at most k objects at any point in time. The problem is known under several names, including the Stacker Crane problem and the Dial-a-Ride problem. No theoretical approximation guarantees were known for this problem other than for the cases k=1, /spl infin/ and the trivial O(k) approximation for general capacity k. We give an algorithm with approximation ratio O(/spl radic/k) for special instances on a class of tree metrics called height-balanced trees. Using Bartal's recent results on the probabilistic approximation of metric spaces by tree metrics, we obtain an approximation ratio of O(/spl radic/k log n log log n) for arbitrary n point metric spaces. When the points lie on a line (line metric), we provide a 2-approximation algorithm. We also consider the Dial-a-Ride problem in another framework: when the vehicle is allowed to leave objects at intermediate locations and pick them up at a later time and deliver them. For this model, we design an approximation algorithm whose performance ratio is O(1) for tree metrics and O(log n log log n) for arbitrary metrics. We also study the ratio between the values of the optimal solutions for the two versions of the problem. 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引用次数: 62
摘要
我们给出了Capacitated call -a- ride问题的第一个非平凡近似算法:给定位于度量空间中点的物体集合,每个物体的指定目的地,以及最多可容纳k个物体的车辆,目标是计算车辆的最短行程,其中所有物体都可以被运送到目的地,同时确保车辆在任何时间点最多携带k个物体。这个问题有几个名字,包括堆垛起重机问题和拨号搭车问题。除了k=1, /spl / /和一般容量k的平凡O(k)近似值之外,这个问题没有已知的理论近似值保证。我们给出了一个近似比为O(/spl /k)的算法,用于一类称为高度平衡树的树度量的特殊实例。利用Bartal最近关于树度量空间的概率逼近的结果,我们得到了任意n点度量空间的近似比为O(/spl基/k log n log log n)。当点位于一条线上(线度量)时,我们提供了一个2逼近算法。我们还在另一个框架中考虑了Dial-a-Ride问题:当车辆被允许将物体留在中间位置,并在稍后的时间取走并交付它们时。对于该模型,我们设计了一种近似算法,其性能比对于树度量为O(1),对于任意度量为O(log n log log n)。我们还研究了两个版本的问题的最优解的值之间的比率。我们表明,与k-delivery TSP中所有对象都相同的情况不同,对于Dial-a-Ride问题,该比率不受常数的限制,它可以大到R(k/sup 2/3/)。
We give the first non-trivial approximation algorithm for the Capacitated Dial-a-Ride problem: given a collection of objects located at points in a metric space, a specified destination point for each object, and a vehicle with a capacity of at most k objects, the goal is to compute a shortest tour for the vehicle in which all objects can be delivered to their destinations while ensuring that the vehicle carries at most k objects at any point in time. The problem is known under several names, including the Stacker Crane problem and the Dial-a-Ride problem. No theoretical approximation guarantees were known for this problem other than for the cases k=1, /spl infin/ and the trivial O(k) approximation for general capacity k. We give an algorithm with approximation ratio O(/spl radic/k) for special instances on a class of tree metrics called height-balanced trees. Using Bartal's recent results on the probabilistic approximation of metric spaces by tree metrics, we obtain an approximation ratio of O(/spl radic/k log n log log n) for arbitrary n point metric spaces. When the points lie on a line (line metric), we provide a 2-approximation algorithm. We also consider the Dial-a-Ride problem in another framework: when the vehicle is allowed to leave objects at intermediate locations and pick them up at a later time and deliver them. For this model, we design an approximation algorithm whose performance ratio is O(1) for tree metrics and O(log n log log n) for arbitrary metrics. We also study the ratio between the values of the optimal solutions for the two versions of the problem. We show that unlike in k-delivery TSP in which all the objects are identical, this ratio is not bounded by a constant for the Dial-a-Ride problem, and it could be as large as R(k/sup 2/3/).