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TSP
2008
166views more  TSP 2008»
13 years 5 months ago
Linear Regression With Gaussian Model Uncertainty: Algorithms and Bounds
In this paper, we consider the problem of estimating an unknown deterministic parameter vector in a linear regression model with random Gaussian uncertainty in the mixing matrix. W...
Ami Wiesel, Yonina C. Eldar, Arie Yeredor
ORL
2008
86views more  ORL 2008»
13 years 5 months ago
Searching the k-change neighborhood for TSP is W[1]-hard
We show that searching the k-change neighborhood is W[1]-hard for metric TSP, which means that finding the best tour in the k-change neighborhood essentially requires complete sea...
Dániel Marx
CORR
2011
Springer
256views Education» more  CORR 2011»
13 years 24 days ago
Approximating Graphic TSP by Matchings
We present a framework for approximating the metric TSP based on a novel use of matchings. Traditionally, matchings have been used to add edges in order to make a given graph Eule...
Tobias Mömke, Ola Svensson
FOCS
1995
IEEE
13 years 9 months ago
An Approximation Scheme for Planar Graph TSP
We consider the special case of the traveling salesman problem TSP in which the distance metric is the shortest-path metric of a planar unweighted graph. We present a polynomial...
Michelangelo Grigni, Elias Koutsoupias, Christos H...
LION
2009
Springer
210views Optimization» more  LION 2009»
14 years 10 days ago
Beam-ACO Based on Stochastic Sampling: A Case Study on the TSP with Time Windows
Beam-ACO algorithms are hybrid methods that combine the metaheuristic ant colony optimization with beam search. They heavily rely on accurate and computationally inexpensive boundi...
Manuel López-Ibáñez, Christia...