Adaptive Plan system using Differential Evolution with Genetic Algorithm

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

1 Citation (Scopus)

Abstract

This paper describes a new proposed strategy of Adaptive Plan System using Differential Evolution (DE) with Genetic Algorithm (GA) called APGA/DE to solve large scale optimization problems, to reduce a large amount of calculation cost, and to improve stability in convergence to an optimal solution. This is an approach that combines the global search ability of GA and Adaptive Plan (AP) for local search ability. The proposed strategy incorporates new concept of AP using DE for Adaptive System (AS) with GA. The APGA/DE is applied to several benchmark functions with multi-dimensions to evaluate its performance. It is shown to be statistically significantly superior to other Evolutionary Algorithms (EAs), and Memetic Algorithms (MAs). We confirmed satisfactory performance through various benchmark tests.

Original languageEnglish
Title of host publicationProceedings - 2013 IEEE International Conference on Industrial Technology, ICIT 2013
Pages40-45
Number of pages6
DOIs
Publication statusPublished - 2013 May 15
Event2013 IEEE International Conference on Industrial Technology, ICIT 2013 - Cape Town, South Africa
Duration: 2013 Feb 252013 Feb 28

Publication series

NameProceedings of the IEEE International Conference on Industrial Technology

Conference

Conference2013 IEEE International Conference on Industrial Technology, ICIT 2013
CountrySouth Africa
CityCape Town
Period13/2/2513/2/28

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Pham, H., Bui, T., & Hasegawa, H. (2013). Adaptive Plan system using Differential Evolution with Genetic Algorithm. In Proceedings - 2013 IEEE International Conference on Industrial Technology, ICIT 2013 (pp. 40-45). [6505645] (Proceedings of the IEEE International Conference on Industrial Technology). https://doi.org/10.1109/ICIT.2013.6505645