The simulation-driven metaheuristic algorithms have been successful in solving numerous
problems compared to their deterministic counterparts. Despite this advantage, the …

For swarm intelligence algorithms, each individual in the swarm represents a solution in the
search space, and it also can be seen as a data sample from the search space. Based on …

Recently, the numerical optimization field has attracted the research community to propose
and develop various metaheuristic optimization algorithms. This paper presents a new …

The difficulty and complexity of the real-world numerical optimization problems has grown
manifold, which demands efficient optimization methods. To date, various metaheuristic …

DE algorithms have outstanding performance in solving complex problems. However, they
also have highlighted the need for an effective approach to alleviating the risk of premature …

This paper presents a novel meta-heuristic algorithm called Ali Baba and the forty thieves
(AFT) for solving global optimization problems. Recall the famous tale of Ali Baba and the …

It is obvious from wider spectrum of successful applications that metaheuristic algorithms are
potential solutions to hard optimization problems. Among such algorithms are swarm-based …

A novel meta-heuristic algorithm named Egret Swarm Optimization Algorithm (ESOA) is
proposed in this paper, which is inspired by two egret species' hunting behavior (Great Egret …

The rapid expansion of medical data poses numerous challenges for Machine Learning
(ML) tasks due to their potential to include excessive noisy, irrelevant, and redundant …

Multi-agent systems and multi-robot systems have been recognized as unique solutions to
complex dynamic tasks distributed in space. Their effectiveness in accomplishing these …