Solving the Travelling Salesman Problem Based on Collaborative Neurodynamic Optimization with Discrete Hopfield Networks

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Detail(s)

Original languageEnglish
Title of host publication11th International Conference on Information Science and Technology (ICIST)
PublisherInstitute of Electrical and Electronics Engineers
Pages456-465
ISBN (Electronic)978-1-6654-1266-7
ISBN (Print)978-1-6654-2941-2
Publication statusPublished - May 2021

Publication series

NameInternational Conference on Information Science and Technology, ICIST
ISSN (Print)2164-4357
ISSN (Electronic)2573-3311

Conference

Title11th International Conference on Information Science and Technology, ICIST 2021
PlaceChina
CityChengdu
Period21 - 23 May 2021

Abstract

This paper addresses the travelling salesman problem (TSP) based on collaborative neurodynamic optimization (CNO). In the CNO approach to TSP, a population of discrete Hopfield networks are employed for searching local optimal solutions and repeatedly reinitialized by using the particle swarm optimization rule towards a global optimal solution. Experimental results for solving four TSP benchmarks are reported to substantiate the efficacy of the CNO approach.

Research Area(s)

  • collaborative neurodynamic optimization, discrete Hopfield network, Travelling salesman problem

Citation Format(s)

Solving the Travelling Salesman Problem Based on Collaborative Neurodynamic Optimization with Discrete Hopfield Networks. / Li, Hongzong; Wang, Jiasen; Wang, Jun.

11th International Conference on Information Science and Technology (ICIST). Institute of Electrical and Electronics Engineers, 2021. p. 456-465 9440588 (International Conference on Information Science and Technology, ICIST).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review