A weighted point-availability time-dependent network is a list of temporal edges, where each temporal edge has an appearing time value, a travel time value, and a cost value. In this paper we consider the single source Pareto problem in weighted point-availability time-dependent networks, which consists of computing, for any destination d, all Pareto optimal pairs (t, c), where t and c are the arrival time and the cost of a path from s to d, respectively (a pair (t, c) is Pareto optimal if there is no path with arrival time smaller than t and cost no worse than c or arrival time no greater than t and better cost). We design and analyse a general algorithm for solving this problem, whose time complexity is O(M log P), where M is the number of temporal edges and P is the maximum number of Pareto optimal pairs for each node of the network. This complexity significantly improves the time complexity of the previously known solution. Our algorithm can be used to solve several different minimum cost path problems in weighted point-availability time-dependent networks with a vast variety of cost definitions, and it can be easily modified in order to deal with the single destination Pareto problem. All our results apply to directed networks, but they can be easily adapted to undirected networks with no edges with zero travel time.
翻译:加权点数取决于时间的网络是一个时间边缘清单, 每个时间边缘都有时间值、 旅行时间值和成本值。 在本文中, 我们考虑加权点数基于时间的网络中单一源Pareto问题, 包括计算任何目的地的所有Pareto最佳配对( t, c), 其中所有Pareto最佳配对( t, t 和 c) 的到达时间和从 s至 d 路径的成本( 双对 ( t, c) 的到达时间分别为Pareto最优, 如果到达时间没有比 t 小的路, 且成本不比 c 或 到达时间差, 也不比 t 和 更便宜, 成本更高 。 我们设计并分析用于解决这一问题的一般算法, 其时间复杂性是 O( M log P), 其中M 是时间边数, 以及 Pareto 最佳对网络的最大零比 。 这一复杂度极大地提高了以前已知解决方案的时间复杂性。 我们的算法可以用来解决加权点依赖时间的网络中的若干最低成本路径问题, 并且可以很容易地将结果应用到 单一的目的地 。