Metaheuristic algorithms are computational intelligence paradigms especially used for
sophisticated solving optimization problems. This chapter aims to review of all …

Flower pollination algorithm (FPA) is a computational intelligence metaheuristic that takes its
metaphor from flowers proliferation role in plants. This paper provides a comprehensive …

In an organization, a group of people working for a common goal may not achieve their goal
unless they organize themselves in a hierarchy called Corporate Rank Hierarchy (CRH) …

In this paper, we proposed an enhanced reptile search algorithm (RSA) for global
optimization and selected optimal thresholding values for multilevel image segmentation …

This paper presents a novel nature-inspired optimization paradigm, named as squirrel
search algorithm (SSA). This optimizer imitates the dynamic foraging behaviour of southern …

This paper proposes a novel global optimization algorithm called Lichtenberg Algorithm
(LA), inspired by the Lichtenberg figures patterns. Optimization is an essential tool to …

Meta-heuristic search algorithms were successfully used to solve a variety of problems in
engineering, science, business, and finance. Meta-heuristic algorithms share common …

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 …

Grey wolf optimizer (GWO) is a very efficient metaheuristic inspired by the hierarchy of the
Canis lupus wolves. It has been extensively employed to a variety of practical applications …

Grey wolf optimizer (GWO) algorithm is a relatively novel population-based optimization
technique that has the advantage of less control parameters, strong global optimization …