Metaheuristic algorithms are an important area of research in artificial intelligence. The
tumbleweed optimization algorithm (TOA) is the newest metaheuristic optimization algorithm …

This study proposes a novel chaotic cuckoo search (CCS) optimization method by
incorporating chaotic theory into cuckoo search (CS) algorithm. In CCS, chaos …

Abstract Butterfly Optimization Algorithm (BOA) is a new comer in the category of nature
inspired metaheuristic algorithms, inspired from food foraging behavior of the butterflies …

This paper introduces a new bio-inspired metaheuristic algorithm called Walrus Optimization
Algorithm (WaOA), which mimics walrus behaviors in nature. The fundamental inspirations …

Abstract The Whale Optimization Algorithm (WOA) is a recently developed meta-heuristic
optimization algorithm which is based on the hunting mechanism of humpback whales …

The gray wolf optimizer (GWO) and the whale optimization algorithm (WOA) are two
esteemed optimization algorithms, and their various modified versions are proposed in …

The diversification (exploration) and intensification (exploitation) are two main attributes of
any population-based metaheuristic algorithm. It is essential for any algorithm that in …

Swarm-based techniques, a form of meta-heuristic techniques, are derived from the swarm
system's social conduct in nature. A newly brought optimization algorithm is Harris Hawks …

Abstract Harris Hawks Optimizer (HHO) is one of the many recent algorithms in the field of
metaheuristics. The HHO algorithm mimics the cooperative behavior of Harris Hawks and …

Chaotic maps have the characteristics of ergodicity and non-repeatability. Owing to these
properties, they provide fast convergence by effectively scanning the search space in a …