Searching for backbones — an efficient parallel algorithm for the traveling salesman problem

The Traveling Salesman Problem (TSP) plays an important role in Operations Research, Applied Mathematics and Computational Physics. We investigated it using a stochastic approach. Studying several solutions of a special TSP we found that many parts of a good solution are the same in all other good s...

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Veröffentlicht in:Computer physics communications Jg. 96; H. 2; S. 173 - 188
Hauptverfasser: Schneider, Johannes, Froschhammer, Christine, Morgenstern, Ingo, Husslein, Thomas, Singer, Johannes Maria
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Amsterdam Elsevier B.V 01.08.1996
Elsevier Science
Schlagworte:
Applied sciences
Backbone
Computational techniques
Computer science; control theory; systems
Degeneracy
Exact sciences and technology
Markov processes
Mathematical methods in physics
Monte Carlo
Monte carlo and statistical methods
Optimization
Other topics of general interest to physicists
Parallel
Physics
Probability theory, stochastic processes, and statistics
Theoretical computing
Threshold accepting
TSP
Backbone
02.70.Lq
89.20.+a
89.80.+h
Parallel
Optimization
89.90.+n
TSP
02.50.Ga
Degeneracy
Monte Carlo
Threshold accepting
02.50.-r
Travelling salesman problem
Parallel processing
Computerized simulation
Algorithms
ISSN:0010-4655, 1879-2944
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:The Traveling Salesman Problem (TSP) plays an important role in Operations Research, Applied Mathematics and Computational Physics. We investigated it using a stochastic approach. Studying several solutions of a special TSP we found that many parts of a good solution are the same in all other good solutions for this problem. In this paper we discuss an efficient parallel method to reduce the TSP to a smaller one by finding these backbones and eliminating them to get even better solutions in a very short time and a few observables of interest corresponding to this parallel approach.
Bibliographie:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0010-4655
1879-2944
DOI:10.1016/0010-4655(96)00062-8