The optimization problems are becoming more complicated, requiring new and efficient
optimization techniques to solve them. Many bio-inspired meta-heuristic algorithms have …

Metaheuristic algorithms based on intelligent rules have been successfully developed and
applied to solve many optimization areas over the past few decades. The sine–cosine …

Abstract The Firefly Algorithm (FA) is a highly efficient population-based optimization
technique developed by mimicking the flashing behavior of fireflies when mating. This article …

This paper proposes a new stochastic optimizer called the Colony Predation Algorithm
(CPA) based on the corporate predation of animals in nature. CPA utilizes a mathematical …

Currently, meta-heuristic algorithms have been widely studied and applied, but balancing
exploration and exploitation remains a challenge. In this study, a novel meta-heuristic …

Over the past years, many efforts have been accomplished to achieve fast and accurate
meta-heuristic algorithms to optimize a variety of real-world problems. This study presents a …

In this paper, a new stochastic optimizer, which is called slime mould algorithm (SMA), is
proposed based on the oscillation mode of slime mould in nature. The proposed SMA has …

The development of efficient optimization algorithms is crucial across various scientific
disciplines. As the complexity and diversity of optimization problems continue to grow …

A large number of intelligent algorithms based on social intelligent behavior have been
extensively researched in the past few decades, through the study of natural creatures, and …

A recent meta-heuristic algorithm called Marine Predators Algorithm (MPA) is enhanced
using Opposition-Based Learning (OBL) termed MPA-OBL to improve their search efficiency …