Approximating Minimum-Cost Connected T-Joins

We design and analyse approximation algorithms for the minimum-cost connected T-join problem: given an undirected graph G = (V;E) with nonnegative costs on the edges, and a subset of nodes T, find (if it exists) a spanning connected subgraph H of minimum cost such that every node in T has odd degree and every node not in T has even degree; H may have multiple copies of any edge of G. Two well-known special cases are the TSP (|T| = 0) and the s-t path TSP (|T| = 2). Recently, An, Kleinberg, and Shmoys [STOC 2012] improved on the long-standing 5/3-approximation guarantee for the latter problem and presented an algorithm based on LP rounding that achieves an approximation guarantee of (1+sqrt(5))/2 < 1.6181. We show that the methods of An et al. extend to the minimum-cost connected T-join problem. They presented a new proof for a 5/3-approximation guarantee for the s-t path TSP; their proof extends easily to the minimum-cost connected T-join problem. Next, we improve on the approximation guarantee of 5/3 by extending their LP-rounding algorithm to get an approximation guarantee of 13/8 = 1.625 for all |T| >= 4. Finally, we focus on the prize-collecting version of the problem, and present a primal-dual algorithm that is "Lagrangian multiplier preserving" and that achieves an approximation guarantee 3 - 2/(|T|-1) when |T| >= 4. Our primal-dual algorithm is a generalization of the known primal-dual 2-approximation for the prize-collecting s-t path TSP. Furthermore, we show that our analysis is tight by presenting instances with |T| >= 4 such that the cost of the solution found by the algorithm is exactly 3 - 2/(|T|-1) times the cost of the constructed dual solution.