A Collaborative Neurodynamic Optimization Algorithm Based on Boltzmann Machines for Solving the Traveling Salesman Problem

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

1 Scopus Citations
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Detail(s)

Original languageEnglish
Title of host publication2021 11th International Conference on Intelligent Control and Information Processing (ICICIP)
PublisherInstitute of Electrical and Electronics Engineers, Inc.
Pages325-333
ISBN (electronic)978-1-6654-2515-5
Publication statusPublished - Dec 2021

Publication series

NameInternational Conference on Intelligent Control and Information Processing, ICICIP

Conference

Title11th International Conference on Intelligent Control and Information Processing (ICICIP 2021)
PlaceChina
CityDali
Period3 - 7 December 2021

Abstract

The traveling salesman problem is known to be NP-hard and has numerous areas of applications. This paper proposes a collaborative neurodynamic optimization algorithm based on Boltzmann machines for solving the traveling salesman problem. A population of Boltzmann machines is employed for local search, and their initial states are repeatedly reinitialized by using the particle swarm optimization update rule for global repositioning. The efficacy of the proposed collaborative neurodynamic optimization algorithm is substantiated on four traveling salesman problem benchmark instances.

Research Area(s)

  • Boltzmann machine, collaborative neurodynamic optimization, Traveling salesman problem

Citation Format(s)

A Collaborative Neurodynamic Optimization Algorithm Based on Boltzmann Machines for Solving the Traveling Salesman Problem. / Li, Hongzong; Wang, Jun.
2021 11th International Conference on Intelligent Control and Information Processing (ICICIP). Institute of Electrical and Electronics Engineers, Inc., 2021. p. 325-333 (International Conference on Intelligent Control and Information Processing, ICICIP).

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review