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Avtomat. i Telemekh., 2015, Issue 3, Pages 125–134 (Mi at14202)  

This article is cited in 1 scientific paper (total in 1 paper)

System Analysis and Operations Research

Approximate algorithms for the traveling salesman problem. II

S. I. Sergeev

Moscow State University of Economics, Statistics, and Informatics, Moscow, Russia

Abstract: We present several approximate algorithms for solving discrete optimization problems. For instance, for the minimum traveling salesman problem we establish bounds on the functionals for the symmetric problem with a value larger than (99.0–99.70) %; for the asymmetric problem, larger than (99.0–99.23) % (experimental estimates). Besides, we propose a different algorithm for the minimum traveling salesman problem that uses both two-index and single-index models.

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English version:
Automation and Remote Control, 2015, 76:3, 472–479

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Presented by the member of Editorial Board: А. А. Лазарев

Received: 28.09.2013

Citation: S. I. Sergeev, “Approximate algorithms for the traveling salesman problem. II”, Avtomat. i Telemekh., 2015, no. 3, 125–134; Autom. Remote Control, 76:3 (2015), 472–479

Citation in format AMSBIB
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    Citing articles on Google Scholar: Russian citations, English citations
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    This publication is cited in the following articles:
    1. Ch. Zhong, Ch. Luo, Zh. Chu, W. Gan, “A continuous Hopfield neural network based on dynamic step for the traveling salesman problem”, IEEE International Joint Conference on Neural Networks, IJCNN 2017, IEEE, 3318–3323  mathscinet  isi
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