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A Three Particles Algorithm for Solving Some Very High Dimensional Benchmark Unconstrained Optimization Problems Using a Fuzzy Fitness Criterium

    https://doi.org/10.1142/S0218488518400068Cited by:0 (Source: Crossref)
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    This article is part of the issue:
    Special Issue on Fuzzy Systems in Economics and Management

    Abstract

    This work focuses predominantly on unconstrained optimization problems and presents an original algorithm (the code can be downloaded from Ref. 1), which is used for solving a variety of benchmark problems whose dimensions range from 2 to 2.5 millions, using only 3 particles. The algorithm was tested in 36 benchmark continuous unconstrained optimization problems, on a total of 312 instances. The results are presented comparing two fitness criteria: crisp and a fuzzy. The numerical results show that the proposed algorithm is able to reach the global optimum in every benchmark problem.

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