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Binary mean-variance mapping optimization algorithm (BMVMO)

Author

Listed:
  • Ali Hakem Al-Saeedi

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

  • OÄŸuz Altun

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

Abstract

Mean-Variance Mapping Optimization (MVMO) is the newest class of the modern meta-heuristic algorithms. The original version of this algorithm is suitable for continuous search problems, so can’t apply it directly to discrete search problems. In this paper, the binary version of the MVMO (BMVMO) algorithm proposed. The proposed Binary Mean-Variance Mapping Optimization algorithm compare with well-known binary meta-heuristic optimization algorithms such, Binary genetic Algorithm, Binary Particles Swarm Optimization, and Binary Bat Algorithm over fifteen benchmark functions conducted to draw a conclusion. The numeric experiments result proves that BMVMO is better performance.

Suggested Citation

  • Ali Hakem Al-Saeedi & OÄŸuz Altun, 2016. "Binary mean-variance mapping optimization algorithm (BMVMO)," Journal of Applied and Physical Sciences, Prof. Vakhrushev Alexander, vol. 2(2), pages 42-47.
    • Handle: RePEc:apb:japsss:2016:p:42-47
    DOI: 10.20474/japs-2.2.3
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    Citations

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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.
    2. Mohamed Seghire Othman Djediden & Hicham Reguieg & Zoulikha Mekkakia Maaza, 2019. "A distributed intrusion detection system based on apache spark and scikit-learn library," Journal of Applied and Physical Sciences, Prof. Vakhrushev Alexander, vol. 5(1), pages 30-36.
    3. Ramcis N. Vilchez, 2019. "Bidirectional Enhanced Selection Sort Algorithm Technique," International Journal of Applied and Physical Sciences, Dr K.Vivehananthan, vol. 5(1), pages 28-35.

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