A cuckoo search algorithm: Effects of coevolution and application in the development of distributed layouts

Abstract

This article presents a cuckoo search algorithm, via Lévy flight, considering the effects of coevolution on the displacement dynamics of animal communities, and applies this algorithm to the development of maximally distributed physical arrangements. Some variables are introduced such as egg weight and the acquired learning of host birds. The results show that the proposed algorithm prevails, in the majority of the interviewed instances, in the degree of distribution in comparison with the classic TARGET and ALVO methods, and with the Genetic Algorithm. The proposed algorithm was shown to be able to obtain a low degree of distribution in a satisfactory computational time, especially in large problems.

Dingo Optimizer: A Nature-Inspired Metaheuristic Approach for Engineering Problems

“…Firefly algorithm [30] Multiobjective firefly [31] Whale optimization algorithm (WOA) [32] Gravitational search algorithm [33] Multiobjective GSA Bat algorithm (BA) [34] Multiobjective Bat Cuckoo search algorithm (CSA) [35] Multiobjective cuckoo Cat swarm algorithm (CSA) [36] Multiobjective CSO…”