3,126 research outputs found

    Phase Transitions and Backbones of the Asymmetric Traveling Salesman Problem

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    In recent years, there has been much interest in phase transitions of combinatorial problems. Phase transitions have been successfully used to analyze combinatorial optimization problems, characterize their typical-case features and locate the hardest problem instances. In this paper, we study phase transitions of the asymmetric Traveling Salesman Problem (ATSP), an NP-hard combinatorial optimization problem that has many real-world applications. Using random instances of up to 1,500 cities in which intercity distances are uniformly distributed, we empirically show that many properties of the problem, including the optimal tour cost and backbone size, experience sharp transitions as the precision of intercity distances increases across a critical value. Our experimental results on the costs of the ATSP tours and assignment problem agree with the theoretical result that the asymptotic cost of assignment problem is pi ^2 /6 the number of cities goes to infinity. In addition, we show that the average computational cost of the well-known branch-and-bound subtour elimination algorithm for the problem also exhibits a thrashing behavior, transitioning from easy to difficult as the distance precision increases. These results answer positively an open question regarding the existence of phase transitions in the ATSP, and provide guidance on how difficult ATSP problem instances should be generated

    Approximating the Regular Graphic TSP in near linear time

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    We present a randomized approximation algorithm for computing traveling salesperson tours in undirected regular graphs. Given an nn-vertex, kk-regular graph, the algorithm computes a tour of length at most (1+7lnkO(1))n\left(1+\frac{7}{\ln k-O(1)}\right)n, with high probability, in O(nklogk)O(nk \log k) time. This improves upon a recent result by Vishnoi (\cite{Vishnoi12}, FOCS 2012) for the same problem, in terms of both approximation factor, and running time. The key ingredient of our algorithm is a technique that uses edge-coloring algorithms to sample a cycle cover with O(n/logk)O(n/\log k) cycles with high probability, in near linear time. Additionally, we also give a deterministic 32+O(1k)\frac{3}{2}+O\left(\frac{1}{\sqrt{k}}\right) factor approximation algorithm running in time O(nk)O(nk).Comment: 12 page

    On the probabilistic min spanning tree Problem

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    We study a probabilistic optimization model for min spanning tree, where any vertex vi of the input-graph G(V,E) has some presence probability pi in the final instance G′ ⊂ G that will effectively be optimized. Suppose that when this “real” instance G′ becomes known, a spanning tree T, called anticipatory or a priori spanning tree, has already been computed in G and one can run a quick algorithm (quicker than one that recomputes from scratch), called modification strategy, that modifies the anticipatory tree T in order to fit G ′. The goal is to compute an anticipatory spanning tree of G such that, its modification for any G ′ ⊆ G is optimal for G ′. This is what we call probabilistic min spanning tree problem. In this paper we study complexity and approximation of probabilistic min spanning tree in complete graphs under two distinct modification strategies leading to different complexity results for the problem. For the first of the strategies developed, we also study two natural subproblems of probabilistic min spanning tree, namely, the probabilistic metric min spanning tree and the probabilistic min spanning tree 1,2 that deal with metric complete graphs and complete graphs with edge-weights either 1, or 2, respectively

    A domination algorithm for {0,1}\{0,1\}-instances of the travelling salesman problem

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    We present an approximation algorithm for {0,1}\{0,1\}-instances of the travelling salesman problem which performs well with respect to combinatorial dominance. More precisely, we give a polynomial-time algorithm which has domination ratio 1n1/291-n^{-1/29}. In other words, given a {0,1}\{0,1\}-edge-weighting of the complete graph KnK_n on nn vertices, our algorithm outputs a Hamilton cycle HH^* of KnK_n with the following property: the proportion of Hamilton cycles of KnK_n whose weight is smaller than that of HH^* is at most n1/29n^{-1/29}. Our analysis is based on a martingale approach. Previously, the best result in this direction was a polynomial-time algorithm with domination ratio 1/2o(1)1/2-o(1) for arbitrary edge-weights. We also prove a hardness result showing that, if the Exponential Time Hypothesis holds, there exists a constant CC such that n1/29n^{-1/29} cannot be replaced by exp((logn)C)\exp(-(\log n)^C) in the result above.Comment: 29 pages (final version to appear in Random Structures and Algorithms

    On the number of kk-cycles in the assignment problem for random matrices

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    We continue the study of the assignment problem for a random cost matrix. We analyse the number of kk-cycles for the solution and their dependence on the symmetry of the random matrix. We observe that for a symmetric matrix one and two-cycles are dominant in the optimal solution. In the antisymmetric case the situation is the opposite and the one and two-cycles are suppressed. We solve the model for a pure random matrix (without correlations between its entries) and give analytic arguments to explain the numerical results in the symmetric and antisymmetric case. We show that the results can be explained to great accuracy by a simple ansatz that connects the expected number of kk-cycles to that of one and two cycles.Comment: To appear in Journal of Statistical Mechanic

    New Inapproximability Bounds for TSP

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    In this paper, we study the approximability of the metric Traveling Salesman Problem (TSP) and prove new explicit inapproximability bounds for that problem. The best up to now known hardness of approximation bounds were 185/184 for the symmetric case (due to Lampis) and 117/116 for the asymmetric case (due to Papadimitriou and Vempala). We construct here two new bounded occurrence CSP reductions which improve these bounds to 123/122 and 75/74, respectively. The latter bound is the first improvement in more than a decade for the case of the asymmetric TSP. One of our main tools, which may be of independent interest, is a new construction of a bounded degree wheel amplifier used in the proof of our results
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