Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant

For a sample of points drawn uniformly from either the d-dimensional torus or the d-cube, d > 2, we define a class of random processes with the property of being asymptotically equivalent in expectation in the two models. Examples include the traveling salesman problem (TSP), the minimum spanning...

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Main Author: Jaillet, Patrick
Format: Working Paper
Language:en_US
Published: Massachusetts Institute of Technology, Operations Research Center 2004
Online Access:http://hdl.handle.net/1721.1/5196
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author Jaillet, Patrick
author_facet Jaillet, Patrick
author_sort Jaillet, Patrick
collection MIT
description For a sample of points drawn uniformly from either the d-dimensional torus or the d-cube, d > 2, we define a class of random processes with the property of being asymptotically equivalent in expectation in the two models. Examples include the traveling salesman problem (TSP), the minimum spanning tree problem (MST), etc. Application of this result helps closing down one open question: We prove that the analytical expression recently obtained by Avram and Bertsimas for the MST constant in the d-torus model is in fact valid for the traditional d-cube model. For the MST, we also extend our result and show that stronger equivalences hold. Finally we present some remarks on the possible use of the d-torus model for exploring rates of convergence for the TSP in the square.
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spelling mit-1721.1/51962019-04-12T08:06:59Z Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant Jaillet, Patrick For a sample of points drawn uniformly from either the d-dimensional torus or the d-cube, d > 2, we define a class of random processes with the property of being asymptotically equivalent in expectation in the two models. Examples include the traveling salesman problem (TSP), the minimum spanning tree problem (MST), etc. Application of this result helps closing down one open question: We prove that the analytical expression recently obtained by Avram and Bertsimas for the MST constant in the d-torus model is in fact valid for the traditional d-cube model. For the MST, we also extend our result and show that stronger equivalences hold. Finally we present some remarks on the possible use of the d-torus model for exploring rates of convergence for the TSP in the square. 2004-05-28T19:27:31Z 2004-05-28T19:27:31Z 1990-11 Working Paper http://hdl.handle.net/1721.1/5196 en_US Operations Research Center Working Paper;OR 234-90 1172143 bytes application/pdf application/pdf Massachusetts Institute of Technology, Operations Research Center
spellingShingle Jaillet, Patrick
Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant
title Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant
title_full Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant
title_fullStr Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant
title_full_unstemmed Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant
title_short Cube versus Torus Models for Combinatorial Optimization Problems and the Euclidean Minimum Spanning Tree Constant
title_sort cube versus torus models for combinatorial optimization problems and the euclidean minimum spanning tree constant
url http://hdl.handle.net/1721.1/5196
work_keys_str_mv AT jailletpatrick cubeversustorusmodelsforcombinatorialoptimizationproblemsandtheeuclideanminimumspanningtreeconstant