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We give improved approximations for two metric Traveling Salesman Problem (TSP) variants. In Ordered TSP (OTSP) we are given a linear ordering on a subset of nodes o₁, , oₖ. The TSP solution must have that o₈+₁ is visited at some point after oᵢ for each 1 i < k. This is the special case of Precedence-Constrained TSP (PTSP) in which the precedence constraints are given by a single chain on a subset of nodes. In k-Person TSP Path (k-TSPP), we are given pairs of nodes (s₁, t₁), , (sₖ, tₖ). The goal is to find an sᵢ-tᵢ path with minimum total cost such that every node is visited by at least one path. We obtain a 3/2 + e^-1 < 1. 878 approximation for OTSP, the first improvement over a trivial +1 approximation where is the current best TSP approximation. We also obtain a 1 + 2 e^-1/2 < 2. 214 approximation for k-TSPP, the first improvement over a trivial 3-approximation. These algorithms both use an adaptation of the Bridge Lemma that was initially used to obtain improved Steiner Tree approximations Byrka et al. , 2013. Roughly speaking, our variant states that the cost of a cheapest forest rooted at a given set of terminal nodes will decrease by a substantial amount if we randomly sample a set of non-terminal nodes to also become terminals such provided each non-terminal has a constant probability of being sampled. We believe this view of the Bridge Lemma will find further use for improved vehicle routing approximations beyond this paper.
Böhm et al. (Tue,) studied this question.