Modified L-SHADE for Single Objective Real-Parameter Optimization

Jia Fong Yeh, Ting Yu Chen, Tsung Che Chiang

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

Abstract

In this paper we address single objective real parameter optimization by using differential evolution (DE). L-SHADE is a well-known DE with success history-based adaptation and linear population size reduction. We propose a modified L-SHADE (mL-SHADE), in which three modifications are made: (1) removal of the terminal value, (2) addition of polynomial mutation, and (3) proposal of a memory perturbation mechanism. Performance of the proposed mL-SHADE is verified by using ten benchmark functions in the CEC2019 100-Digit Challenge. The results show that mL-SHADE achieves a higher score than seven state-of-the-art adaptive evolutionary algorithms.

Original languageEnglish
Title of host publication2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages381-386
Number of pages6
ISBN (Electronic)9781728121536
DOIs
Publication statusPublished - 2019 Jun
Event2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Wellington, New Zealand
Duration: 2019 Jun 102019 Jun 13

Publication series

Name2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings

Conference

Conference2019 IEEE Congress on Evolutionary Computation, CEC 2019
CountryNew Zealand
CityWellington
Period19/6/1019/6/13

Keywords

  • adaptive
  • differential evolution
  • success history

ASJC Scopus subject areas

  • Computational Mathematics
  • Modelling and Simulation

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  • Cite this

    Yeh, J. F., Chen, T. Y., & Chiang, T. C. (2019). Modified L-SHADE for Single Objective Real-Parameter Optimization. In 2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings (pp. 381-386). [8789991] (2019 IEEE Congress on Evolutionary Computation, CEC 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2019.8789991