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Multiobjective optimization at evolutionary search with binary choice relations. (English. Russian original) Zbl 1454.90082

Cybern. Syst. Anal. 56, No. 3, 449-454 (2020); translation from Kibern. Sist. Anal. 2020, No. 3, 122-128 (2020).
Summary: 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.

MSC:

90C29 Multi-objective and goal programming
90C59 Approximation methods and heuristics in mathematical programming
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References:

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