431 research outputs found

    Shorter tours and longer detours: Uniform covers and a bit beyond

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    Motivated by the well known four-thirds conjecture for the traveling salesman problem (TSP), we study the problem of {\em uniform covers}. A graph G=(V,E)G=(V,E) has an α\alpha-uniform cover for TSP (2EC, respectively) if the everywhere α\alpha vector (i.e. {α}E\{\alpha\}^{E}) dominates a convex combination of incidence vectors of tours (2-edge-connected spanning multigraphs, respectively). The polyhedral analysis of Christofides' algorithm directly implies that a 3-edge-connected, cubic graph has a 1-uniform cover for TSP. Seb\H{o} asked if such graphs have (1−ϵ)(1-\epsilon)-uniform covers for TSP for some ϵ>0\epsilon > 0. Indeed, the four-thirds conjecture implies that such graphs have 8/9-uniform covers. We show that these graphs have 18/19-uniform covers for TSP. We also study uniform covers for 2EC and show that the everywhere 15/17 vector can be efficiently written as a convex combination of 2-edge-connected spanning multigraphs. For a weighted, 3-edge-connected, cubic graph, our results show that if the everywhere 2/3 vector is an optimal solution for the subtour linear programming relaxation, then a tour with weight at most 27/19 times that of an optimal tour can be found efficiently. Node-weighted, 3-edge-connected, cubic graphs fall into this category. In this special case, we can apply our tools to obtain an even better approximation guarantee. To extend our approach to input graphs that are 2-edge-connected, we present a procedure to decompose an optimal solution for the subtour relaxation for TSP into spanning, connected multigraphs that cover each 2-edge cut an even number of times. Using this decomposition, we obtain a 17/12-approximation algorithm for minimum weight 2-edge-connected spanning subgraphs on subcubic, node-weighted graphs

    Robust Branch-Cut-and-Price for the Capacitated Minimum Spanning Tree Problem over a Large Extended Formulation

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    This paper presents a robust branch-cut-and-price algorithm for the Capacitated Minimum Spanning Tree Problem (CMST). The variables are associated to q-arbs, a structure that arises from a relaxation of the capacitated prize-collecting arbores- cence problem in order to make it solvable in pseudo-polynomial time. Traditional inequalities over the arc formulation, like Capacity Cuts, are also used. Moreover, a novel feature is introduced in such kind of algorithms. Powerful new cuts expressed over a very large set of variables could be added, without increasing the complexity of the pricing subproblem or the size of the LPs that are actually solved. Computational results on benchmark instances from the OR-Library show very signi¯cant improvements over previous algorithms. Several open instances could be solved to optimalityNo keywords;

    On vertex adjacencies in the polytope of pyramidal tours with step-backs

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    We consider the traveling salesperson problem in a directed graph. The pyramidal tours with step-backs are a special class of Hamiltonian cycles for which the traveling salesperson problem is solved by dynamic programming in polynomial time. The polytope of pyramidal tours with step-backs PSB(n)PSB (n) is defined as the convex hull of the characteristic vectors of all possible pyramidal tours with step-backs in a complete directed graph. The skeleton of PSB(n)PSB (n) is the graph whose vertex set is the vertex set of PSB(n)PSB (n) and the edge set is the set of geometric edges or one-dimensional faces of PSB(n)PSB (n). The main result of the paper is a necessary and sufficient condition for vertex adjacencies in the skeleton of the polytope PSB(n)PSB (n) that can be verified in polynomial time.Comment: in Englis

    Survivable Networks, Linear Programming Relaxations and the Parsimonious Property

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    We consider the survivable network design problem - the problem of designing, at minimum cost, a network with edge-connectivity requirements. As special cases, this problem encompasses the Steiner tree problem, the traveling salesman problem and the k-connected network design problem. We establish a property, referred to as the parsimonious property, of the linear programming (LP) relaxation of a classical formulation for the problem. The parsimonious property has numerous consequences. For example, we derive various structural properties of these LP relaxations, we present some algorithmic improvements and we perform tight worstcase analyses of two heuristics for the survivable network design problem

    Degree-bounded generalized polymatroids and approximating the metric many-visits TSP

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    In the Bounded Degree Matroid Basis Problem, we are given a matroid and a hypergraph on the same ground set, together with costs for the elements of that set as well as lower and upper bounds f(ε)f(\varepsilon) and g(ε)g(\varepsilon) for each hyperedge ε\varepsilon. The objective is to find a minimum-cost basis BB such that f(ε)≤∣B∩ε∣≤g(ε)f(\varepsilon) \leq |B \cap \varepsilon| \leq g(\varepsilon) for each hyperedge ε\varepsilon. Kir\'aly et al. (Combinatorica, 2012) provided an algorithm that finds a basis of cost at most the optimum value which violates the lower and upper bounds by at most 2Δ−12 \Delta-1, where Δ\Delta is the maximum degree of the hypergraph. When only lower or only upper bounds are present for each hyperedge, this additive error is decreased to Δ−1\Delta-1. We consider an extension of the matroid basis problem to generalized polymatroids, or g-polymatroids, and additionally allow element multiplicities. The Bounded Degree g-polymatroid Element Problem with Multiplicities takes as input a g-polymatroid Q(p,b)Q(p,b) instead of a matroid, and besides the lower and upper bounds, each hyperedge ε\varepsilon has element multiplicities mεm_\varepsilon. Building on the approach of Kir\'aly et al., we provide an algorithm for finding a solution of cost at most the optimum value, having the same additive approximation guarantee. As an application, we develop a 1.51.5-approximation for the metric Many-Visits TSP, where the goal is to find a minimum-cost tour that visits each city vv a positive r(v)r(v) number of times. Our approach combines our algorithm for the Bounded Degree g-polymatroid Element Problem with Multiplicities with the principle of Christofides' algorithm from 1976 for the (single-visit) metric TSP, whose approximation guarantee it matches.Comment: 17 page
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