一种策略路由框架及备选路径计算算法
A Strategic Routing Framework and Algorithms for Computing Alternative Paths
摘要：
传统的导航服务为单个驾驶员找到最快的路线。尽管总是使用最快的路线似乎对每个人都是可取的，但自私的行为可能会产生不良影响，例如更高的能源消耗和可避免的拥堵，甚至导致更高的整体和个人旅行时间。相比之下，战略路由的目的是优化交通的所有代理关于一个全局优化目标。我们引入了一个框架，正式现实世界的战略路由方案的算法问题，并研究其中之一，我们称之为单一的替代路径（SAP），详细。在那里，我们得到了一个单一的起点-目的地对之间的原始路线。我们的目标是建议一个替代路线的所有代理，优化整体旅行时间的假设下，代理分布在两条路线根据心理模型，我们引入帕累托一致性的概念。我们表明，SAP问题是NP完全的，即使是这样的模型。尽管如此，假设帕累托一致性，我们给多个算法的SAP的不同变种，使用多标准的最短路径算法作为子程序。此外，我们证明了几个自然模型实际上是帕累托符合。我们的算法的实现作为一个概念证明，表明SAP可以解决在合理的时间，即使算法在最坏的情况下有指数级的运行时间。
英文摘要：
Traditional navigation services find the fastest route for a single driver. Though always using the fastest route seems desirable for every individual, selfish behavior can have undesirable effects such as higher energy consumption and avoidable congestion, even leading to higher overall and individual travel times. In contrast, strategic routing aims at optimizing the traffic for all agents regarding a global optimization goal. We introduce a framework to formalize real-world strategic routing scenarios as algorithmic problems and study one of them, which we call Single Alternative Path (SAP), in detail. There, we are given an original route between a single origin--destination pair. The goal is to suggest an alternative route to all agents that optimizes the overall travel time under the assumption that the agents distribute among both routes according to a psychological model, for which we introduce the concept of Pareto-conformity. We show that the SAP problem is NP-complete, even for such models. Nonetheless, assuming Pareto-conformity, we give multiple algorithms for different variants of SAP, using multi-criteria shortest path algorithms as subroutines. Moreover, we prove that several natural models are in fact Pareto-conform. The implementation of our algorithms serves as a proof of concept, showing that SAP can be solved in reasonable time even though the algorithms have exponential running time in the worst case.
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