This article is cited in 1 paper

System, evolutionary, cognitive modeling

Hybrid algorithm for mixed multi-objective optimization “cuckoo search” with genetic crossover operator

K. S. Sarin

Tomsk State University of Control Systems and Radioelectronics

Abstract: The article proposes a mixed-integer multi-objective optimization algorithm based on the cuckoo search metaheuristic and the genetic crossover operator. Search in discrete space is carried out using a genetic operator, and in continuous space using a metaheuristic strategy. Performance was assessed using modified ZDT and DTLZ tests with mixed variables. The experimental results showed the high efficiency of the proposed algorithm on complex estimates of convergence and diversity.

Keywords: optimization methods, multi-objective optimization, metaheuristics, stochastic algorithms, evolutionary intelligence, swarm intelligence, mixed optimization, genetic algorithm, cuckoo search, hybrid algorithm.

DOI: 10.14357/20718594240207

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