We introduce the $L_p$ Traveling Salesman Problem ($L_p$-TSP), given by an origin, a set of destinations, and underlying distances. The objective is to schedule a destination visit sequence for a traveler of unit speed to minimize the Minkowski $p$-norm of the resulting vector of visit/service times. For $p = \infty$ the problem becomes a path variant of the TSP, and for $p = 1$ it defines the Traveling Repairman Problem (TRP), both at the center of classical combinatorial optimization. We provide an approximation preserving polynomial-time reduction of $L_p$-TSP to the segmented-TSP Problem [Sitters '14] and further study the case of $p = 2$, which we term the Traveling Firefighter Problem (TFP), when the cost due to a delay in service is quadratic in time. We also study the all-norm-TSP problem [Golovin et al. '08], in which the objective is to find a route that is (approximately) optimal with respect to the minimization of any norm of the visit times, and improve corresponding (in)approximability bounds on metric spaces.
翻译:我们引入了由来源、一组目的地和基本距离提供的$L_p$ 旅行推销员问题(L_p$-TSP), 由来源、 一组目的地和基本距离提供。 我们的目标是为单位速度的旅行者安排一个目的地访问序列,以最大限度地减少由此导致的访问/服务时间矢量的Minkowski $p$-norm。 $p=\infty$ 问题成为TSP的路径变体, $p= = 1美元, 它定义了旅行修理员问题(TRP ), 两者都位于古典组合优化中心。 我们的目标是为分段- TSP 问题[SITP '14] 提供一个保存$_ p$- TSP 的超时速削减近似点, 并进一步研究 $p = 2美元的情况, 我们称之为旅行消防员问题(TFP), 当服务延误的成本在时间上是四倍的。 我们还研究了全温- TSP 问题[Golovin et al.08], 其目标在于找到一条途径, 该途径是(在任何标准上的最佳访问时间上) 最佳地(接近最佳地),,, 任何最接近于任何最接近于最起码地访问。