A Genetic Algorithm for Finding Regular Graphs with Minimum Average Shortest Path Length

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem of finding a simple regular graph with the specified order and degree that minimizes the average shortest path length has a long history in graph theory. Recently this problem has attracted a great deal of attention in relation to the design of computer networks in data centers. In this paper, we propose a genetic algorithm for finding an approximate solution to this problem. Because the search space is the set of all simple regular graphs with the specified order and degree, conventional genetic algorithms cannot be directly applied. We propose in this paper new crossover and mutation operators that guarantee the simplicity and regularity of graphs. We also evaluate the effectiveness of the proposed method experimentally.

Original languageEnglish
Title of host publication2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2431-2436
Number of pages6
ISBN (Electronic)9781728125473
DOIs
Publication statusPublished - Dec 1 2020
Event2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020 - Virtual, Canberra, Australia
Duration: Dec 1 2020Dec 4 2020

Publication series

Name2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020

Conference

Conference2020 IEEE Symposium Series on Computational Intelligence, SSCI 2020
CountryAustralia
CityVirtual, Canberra
Period12/1/2012/4/20

Keywords

  • crossover
  • generalized Moore graph
  • genetic algorithm
  • mutation
  • regular graph

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Decision Sciences (miscellaneous)

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