A deterministic connectionist machine for the traveling salesman problem

Jun Wang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Citations (Scopus)

Abstract

A deterministic connectionist machine for solving the traveling salesman problem (TSP) is proposed. The original TSP is reformulated as a penalty problem, i.e., an unconstrained nonlinear programming problem with penalty terms. A deterministic connectionist machine is designed to realize the solution procedure for the penalty problem. The major feature of the machine is that the penalty parameter increases as the states evolve, so the generated tours are always valid. The stability of state trajectories and feasibility of the generated solutions for the proposed connectionist machine are theoretically and practically justified. A simulation algorithm is presented, and numerical simulations results are reported. They show that the motion of the state is always asymptotically stable, the generated tours are always valid and near-optimal if not optimal, and the solution procedure is fairly robust to the selection of the step length, initial state, and initial penalty parameter.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Conference on Systems, Man and Cybernetics
PublisherPubl by IEEE
Pages374-375
Number of pages2
ISBN (Print)0879425970
Publication statusPublished - Nov 1990
Externally publishedYes
Event1990 IEEE International Conference on Systems, Man, and Cybernetics - Los Angeles, CA, USA
Duration: 4 Nov 19907 Nov 1990

Publication series

NameProceedings of the IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)0884-3627

Conference

Conference1990 IEEE International Conference on Systems, Man, and Cybernetics
CityLos Angeles, CA, USA
Period4/11/907/11/90

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