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Numerical Studies Of Some Generalized Controlled Random Search Algorithms

Author

Listed:
  • P. KAELO

    (Department of Mathematics, University of Botswana, Private Bag UB00704, Gaborone, Botswana)

  • M. M. ALI

    (School of Computational and Applied Mathematics, Witwatersrand University, Wits 2050, Johannesburg, South Africa)

Abstract

This paper presents motivations and algorithmic details of some generalized controlled random search (CRS) algorithms for global optimization. It also carries out an extensive numerical study of the generalized CRS algorithms to demonstrate their superiorities over their original counterparts. The numerical study is carried out using a set of 50 test problems many of which are inspired by practical applications. Numerical experiments indicate that the generalized algorithms are considerably better than the previous versions. The algorithms are also compared with the DIRECT algorithm (Jones et al., 1993). The comparison shows that the generalized CRS algorithms are better than the DIRECT algorithm in high dimensional problems. Thus, they offer a reasonable alternative to many currently available stochastic algorithms, especially for problems requiring "direct search type" methods.

Suggested Citation

  • P. Kaelo & M. M. Ali, 2012. "Numerical Studies Of Some Generalized Controlled Random Search Algorithms," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 29(02), pages 1-24.
    • Handle: RePEc:wsi:apjorx:v:29:y:2012:i:02:n:s0217595912500169
    DOI: 10.1142/S0217595912500169
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