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Two enhanced differential evaluation algorithms for expensive optimization

Author

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  • Muneer Maaroof Hasan

    (Computer Engineering Department, Yildiz Technical University, Istanbul, Turkey)

  • OÄŸuz Altun

    (Computer Engineering Department, Yildiz Technical University, Istanbul, Turkey)

Abstract

In this paper, the meta-heuristic algorithm which named Differential Evaluation (DE) has been improved. The improving made to increase the exploration rate and decrease the run time. Since DE needs too long time, when we implement it to solve computational expensive problems, we developed two different versions of DE named by Enhanced1 Differential Evaluation (E1DE) and Enhanced2 Differential Evaluation (E2DE). E1DE and E2DE were introduced to solve Computationally Expensive Optimization (CEO). Problems discussed and tested using all 15 test functions of the Special Session & Competition on Real-Parameter Single Objective Optimization (Expensive Case) at Congress on Evolutionary Computation 2015 (CEC-2015). The results show that the work significantly improved the basic DE in time by 54% and in results by 86%

Suggested Citation

  • Muneer Maaroof Hasan & OÄŸuz Altun, 2016. "Two enhanced differential evaluation algorithms for expensive optimization," Journal of Applied and Physical Sciences, Prof. Vakhrushev Alexander, vol. 2(2), pages 48-53.
    • Handle: RePEc:apb:japsss:2016:p:48-53
    DOI: 10.20474/japs-2.2.4
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    Cited by:

    1. Jiahui Chen, 2018. "The Application of tree-based ML algorithm in steel plates Ffaults identification," Journal of Applied and Physical Sciences, Prof. Vakhrushev Alexander, vol. 4(2), pages 47-54.

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