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Application of the New FAAO Metaheuristics in Modeling and Simulation of the Search for the Optimum of a Function with Many Extremes

  • Jacek M. CzerniakEmail author
  • Dawid Ewald
  • Hubert Zarzycki
  • Piotr Augustyn
Conference paper
  • 9 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1081)

Abstract

The article presents a new multi-criteria optimization method called Fuzzy Artificial Acari Optimization (FAAO). The AAO method was tested using ten commonly known benchmarks functionssuch as; Sphere - with a uniform surface, having only one minimum, Ackley - with a relatively uniform surface, having several dozen local minima and one global maximum with a much smaller value than most local minima, Eggholder -with an uneven surface, several dozen local minima, values similar to its global minimum global and Easom - with a flat surface in the vast majority of the domain, with global minimum of small area relative to the search space. The results were compared with other representatives of the Swarm Intelligence trend, such as ABC, PSO. It is very important to observe that FAAO is almost always the fastest, which can be treated as a good prognosis in the future applications of this metaheuristic.

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Copyright information

© Springer Nature Switzerland AG 2021

Authors and Affiliations

  • Jacek M. Czerniak
    • 1
    Email author
  • Dawid Ewald
    • 1
  • Hubert Zarzycki
    • 2
  • Piotr Augustyn
    • 1
  1. 1.Department of Computer ScienceCasimir the Great University in BydgoszczBydgoszczPoland
  2. 2.University of Information Technology and Management CopernicusWroclawPoland

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