Opposition-based differential evolution (ODE) with variable jumping rate

S. Rahnamayan, H. R. Tizhoosh, M. M.A. Salama

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

Abstract

In this paper, a time varying jumping rate (TVJR) model for Opposition-Based Differential Evolution (ODE) has been proposed. According to this model, the jumping rate changes linearly during the evolution based on the number of function evaluations. A test suite with 15 well-known benchmark functions has been employed to compare performance of the DE and ODE with variable jumping rate settings. Results show that a higher jumping rate is more desirable during the exploration than during the exploitation. Details for the proposed approach and the conducted experiments are provided.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007
Pages81-88
Number of pages8
DOIs
StatePublished - 2007
Event2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007 - Honolulu, HI, United States
Duration: Apr 1 2007Apr 5 2007

Publication series

NameProceedings of the 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007

Conference

Conference2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007
Country/TerritoryUnited States
CityHonolulu, HI
Period4/1/074/5/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Mathematics(all)

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