An improved African buffalo optimization algorithm using chaotic map and chaotic-levy flight

  • Authors

    • Chinwe Peace Igiri Amity Institute of Information Technology, Amity University Rajasthan, India
    • Yudhveer Singh Amity Institute of Information Technology, Amity University Rajasthan, India
    • Deepshikha Bhargava School of Computer Science, University of Petroleum and Energy Studies, Dehradun, India
    2018-11-15
    https://doi.org/10.14419/ijet.v7i4.22726
  • Chaotic Optimization, African Buffalo Optimization, Levy-Flight, Non-Linear Optimization, Meta-Heuristics.

  • Abstract

    Optimization is ever-growing research that cuts across all walks of life. Many popular metaheuristic algorithms have metamorphosed into numerous variants in search of the sophisticated kernel for optimal solution. The African Buffalo optimization (ABO) algorithm is one of the fastest metaheuristic algorithms. This algorithm is inspired by the alarm and alert calls of African buffaloes during their foraging and defending activities. The present study investigates the strengths and weaknesses of ABO and proposes two improvement strategies: Chaotic ABO (CABO) and chaotic-levy flight ABO (CLABO). The results are validated with ten benchmark optimization problems and compared with other metaheuristic algorithms in the literature. Further, the CABO and CLABO algorithms are ranked first and second, respectively. This proves the superiority of the proposed improved algorithms over others under this study. Finally, the improved chaotic ABO would be utilized for optimizing industrial scheduling for oil and gas in our future work.

     

     

     

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  • How to Cite

    Peace Igiri, C., Singh, Y., & Bhargava, D. (2018). An improved African buffalo optimization algorithm using chaotic map and chaotic-levy flight. International Journal of Engineering & Technology, 7(4), 4570-4576. https://doi.org/10.14419/ijet.v7i4.22726

    Received date: 2018-12-01

    Accepted date: 2018-12-01

    Published date: 2018-11-15