Triple and quadruple comparison-based interactive differential evolution and differential evolution

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

19 Citations (Scopus)

Abstract

We propose a triple comparison and a quadruple comparison based mechanism for enhancing differential evolution (DE), especially for interactive DE (IDE) where the method can be used to reduce IDE user fatigue. Besides the target vector and trial vector from normal DE, opposition vectors generated by opposition-based learning are used to determine offspring, and the best vector from among these three or four vectors becomes offspring for the next generation. We evaluate the proposed methods by comparing them with conventional IDE and conventional opposition-based IDE using a simulated IDE modeled using a four dimensional Gaussian mixture model. We also evaluate them in DE using 24 benchmark functions. The experiments show that our proposed methods can enhance IDE and DE search efficiently according to several evaluation indices. These include the converged fitness values after the same number of generations, converged fitness values after the same number of fitness calculations, fitness calculation cost, convergence success rates and acceleration rates.

Original languageEnglish
Title of host publicationFOGA 2013 - Proceedings of the 12th ACM Workshop on Foundations of Genetic Algorithms
Pages173-182
Number of pages10
DOIs
Publication statusPublished - Apr 15 2013
Event12th ACM Workshop on Foundations of Genetic Algorithms, FOGA 2013 - Adelaide, SA, Australia
Duration: Jan 16 2013Jan 20 2013

Publication series

NameFOGA 2013 - Proceedings of the 12th ACM Workshop on Foundations of Genetic Algorithms

Other

Other12th ACM Workshop on Foundations of Genetic Algorithms, FOGA 2013
CountryAustralia
CityAdelaide, SA
Period1/16/131/20/13

All Science Journal Classification (ASJC) codes

  • Discrete Mathematics and Combinatorics

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  • Cite this

    Pei, Y., & Takagi, H. (2013). Triple and quadruple comparison-based interactive differential evolution and differential evolution. In FOGA 2013 - Proceedings of the 12th ACM Workshop on Foundations of Genetic Algorithms (pp. 173-182). (FOGA 2013 - Proceedings of the 12th ACM Workshop on Foundations of Genetic Algorithms). https://doi.org/10.1145/2460239.2460255