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

Harmony search algorithm is the recently developed metaheuristic in the last decade. It
mimics the behavior of a musician producing a perfect harmony. It has been used to solve …

Metaheuristics are an impressive area of research with extremely important improvements in
the solution of intractable optimization problems. Major advances have been made since the …

Nowadays, the use of metaheuristic algorithms has dramatically increased in order to
achieve the optimal solution in solving continuous optimization problems. In this paper, a …

Artificial bee colony (ABC) algorithm invented recently by Karaboga is a biological-inspired
optimization algorithm, which has been shown to be competitive with some conventional …

Feature selection is a process to reduce the dimension of a dataset by removing redundant
features, and to use the optimal subset of features for machine learning or data mining …

This paper presents a physics-inspired metaheuristic optimization algorithm, known as
Electromagnetic Field Optimization (EFO). The proposed algorithm is inspired by the …

In this paper, the algorithmic concepts of the Cuckoo-search (CK), Particle swarm
optimization (PSO), Differential evolution (DE) and Artificial bee colony (ABC) algorithms …

This paper thoroughly reviews and analyzes the main characteristics and application
portfolio of the so-called Harmony Search algorithm, a meta-heuristic approach that has …

To overcome the limitation of single search strategy of grey wolf optimizer (GWO) in solving
various function optimization problems, we propose a multi-strategy ensemble GWO …