Performance analysis of vegetation evolution

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

2 Citations (Scopus)

Abstract

We focus on analyzing the impact of operations of a proposed Vegetation evolution (VEGE) algorithm on its performance rather than compare it with other EC algorithms, i.e., investigate the impact of each component of the VEGE algorithm on its performance. To further analyze the performance of VEGE algorithm, we design a series of controlled experiments to investigate the contribution of each VEGE component by running them on 28 benchmark functions of 3 different dimensions. Subsequently, we summarize some our experiences on setting VEGE parameters to apply the VEGE to optimization tasks. The experimental results reveal that the maturity operation has a critical impact on performance and the number of growth operations of an individual is set as small as possible, while the number of generated seed individuals is not an important factor. Besides, we discover that population size should be gradually increased as the dimension increases. Finally, we point out several potential research directions.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2214-2219
Number of pages6
ISBN (Electronic)9781728145693
DOIs
Publication statusPublished - Oct 2019
Event2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019 - Bari, Italy
Duration: Oct 6 2019Oct 9 2019

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Volume2019-October
ISSN (Print)1062-922X

Conference

Conference2019 IEEE International Conference on Systems, Man and Cybernetics, SMC 2019
CountryItaly
CityBari
Period10/6/1910/9/19

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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