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The k-Delivery Traveling Salesman Problem: Revisited

机译:k送货旅行推销员问题:重新审视

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The k-delivery Travelling Salesman Problem (k-dTSP) is one of the most interesting variants of vehicle routing. Given a weighted graph, on which each node either holds an item or requires an item, and a vehicle of capacity of k which can carry at most k items at a time, one is asked to schedule a shortest route for the vehicle so that it starts from a depot and transports all items from the points holding them to the points requiring items, and returns home under the vehicle capacity constraint. It is clearly an NP-hard problem. Among quite a few results the best-known approximation algorithm is due to Charikar, Menuier and Raghavachari (2001). All the previous approaches first construct an approximate TSP tour. It is then expanded to a (much) larger but bounded one by repeatedly moving the vehicle on the tour, so that the pickup/delivery tasks can be completed. It motivates us to consider a simpler approach, that directly applies an optimal algorithm on a circle graph after we derive an approximate TSP tour. It is known that k-dTSP on a path graph is polynomially solvable, while the complexity is open on a circle graph. In this paper, we settle this issue by presenting a polynomial algorithm on a circle, and then apply it to k-dTSP on general graphs. Although the theoretical bound is yet unclear, experiments show that it outperforms the existing approaches.
机译:K-oversion旅行推销员问题(K-DTSP)是车辆路由最有趣的变体之一。给定加权图,每个节点都保存物品或需要一个项目,并且一次可以一次携带最多k项的容量的车辆,一个人被要求安排车辆的最短路线以便它从仓库开始,并将所有物品传输到将它们的点,将它们持有到需要物品的点,并在车辆容量约束下返回回家。显然是一个难题的问题。在相当多的结果中,最着名的近似算法是由于Charikar,菜单和Raghavachari(2001)。所有以前的方法首先构建一个近似的TSP巡回赛。然后将其扩展到(多)较大但是通过重复移动车辆在巡视上移动,从而可以完成拾取/送货任务。它激励我们考虑更简单的方法,在我们推导近似TSP巡回赛之后,直接在圆图上应用最佳算法。众所周知,路径图上的K-DTSP是多项式可溶的,而复杂性在圆形图上打开。在本文中,我们通过在圆上呈现多项式算法来解决这个问题,然后在一般图表上将其应用于K-DTSP。虽然理论界限尚不清楚,但实验表明它优于现有的方法。

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