Throughout the last decade, high-dimensional function optimization problems have received
substantial research interest in the field of intelligence computation. Butterfly optimization …

ABSTRACT Butterfly Optimisation Algorithm (BOA) is a kind of meta-heuristic swarm
intelligence algorithm based on butterfly foraging strategy, but it still needs to be improved in …

For data mining tasks on high-dimensional data, feature selection is a necessary pre-
processing stage that plays an important role in removing redundant or irrelevant features …

Butterfly optimization algorithm (BOA), as a recently proposed meta-heuristic optimization
technique, performs competitively in solving numerical optimization problems as well as real …

To solve complex high-dimensional optimization problems, an opposition-based butterfly
optimization algorithm with adaptive elite mutation (OBOAEM) is proposed. In the initial …

In this paper, a surrogate-assisted hybrid swarm optimization algorithm is proposed to solve
high-dimensional computationally expensive problems. Two swarms are, respectively, used …

To solve high-dimensional function optimization problems, many evolutionary algorithms
have been proposed. In this paper, we propose a new cooperative coevolution orthogonal …

Whale optimization algorithm was developed based on the prey-catching characteristics of
the humpback whales. Due to its simple structure and efficiency, the researchers employed …

Feature selection is an important data processing method to reduce dimension of the raw
datasets while preserving the information as much as possible. In this paper, an enhanced …

To solve large-scale optimization problems, Fragrance coefficient and variant Particle
Swarm local search Butterfly Optimization Algorithm (FPSBOA) is proposed. In the position …