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Multiobjective Optimization at Evolutionary Search with Binary Choice Relations

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Cybernetics and Systems Analysis Aims and scope

Abstract

A multiobjective optimization problem is considered, in which binary choice relations are used instead of optimized functions. To solve this problem, it is proposed to use an evolutionary random search algorithm, in which the function of choice in the form of a lock is used instead of the choice function in the form of a preference,. The convergence of the proposed evolutionary algorithms is analyzed, and sufficient conditions for convergence are formulated. The results of the proposed evolutionary search are compared with the results of well-known evolutionary algorithms for one test problem.

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Authors and Affiliations

  1. Prydniprovska State Academy of Civil Engineering and Architecture, Dnipro, Ukraine

    V. F. Irodov, R. V. Barsuk & H. Ya. Chornomorets

Authors
  1. V. F. Irodov
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  2. R. V. Barsuk
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  3. H. Ya. Chornomorets
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Correspondence to V. F. Irodov, R. V. Barsuk or H. Ya. Chornomorets.

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Translated from Kibernetika i Sistemnyi Analiz, No. 3, May–June, 2020, pp. 122–128.

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Irodov, V.F., Barsuk, R.V. & Chornomorets, H.Y. Multiobjective Optimization at Evolutionary Search with Binary Choice Relations. Cybern Syst Anal 56, 449–454 (2020). https://doi.org/10.1007/s10559-020-00260-7

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  • DOI: https://doi.org/10.1007/s10559-020-00260-7

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