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An immune genetic algorithm based on immune regulation

  • University of Science and Technology of China

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

Abstract

Using immune regulation mechanisms that include density regulation and network regulation, this paper proposes a novel immune genetic algorithm. Its core idea is that all individuals compose an antibody network, and it utilizes a density regulation mechanism to adjust individual diversity at an individual level and network regulation mechanism to achieve dynamic balance between individual diversity and population convergence. The dynamic regulative ability of this algorithm is analyzed and the approach to choosing the parameters is also given. As a novel adaptive resolving algorithm, it can be used to solve many complex optimization problems. This paper discusses solution of the frequency assignment problem and analyzes the parameters' influence upon the performance of this algorithm. The experimental results prove that this algorithm has good performance and can properly maintain the balance between individual diversity and population convergence.

Original languageEnglish
Title of host publicationProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002
PublisherIEEE Computer Society
Pages801-806
Number of pages6
ISBN (Print)0780372824, 9780780372825
DOIs
StatePublished - 2002
Externally publishedYes
Event2002 Congress on Evolutionary Computation, CEC 2002 - Honolulu, HI, United States
Duration: 12 May 200217 May 2002

Publication series

NameProceedings of the 2002 Congress on Evolutionary Computation, CEC 2002
Volume1

Conference

Conference2002 Congress on Evolutionary Computation, CEC 2002
Country/TerritoryUnited States
CityHonolulu, HI
Period12/05/0217/05/02

Keywords

  • density regulation
  • frequency assignment
  • Immune genetic algorithm
  • network regulation

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