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

Multi-population based nature-inspired optimization algorithms have attracted wide research
interests in the last decade, and become one of the frequently used methods to handle real …

Many optimization problems in reality involve both continuous and discrete decision
variables, and these problems are called mixed-variable optimization problems (MVOPs) …

Nature has been considered as an inspiration of several recent meta-heuristic algorithms.
This paper firstly studies and mimics the behavior of Scottish red deer in order to develop a …

The first powerful variant of the Harris hawks optimization (HHO) is proposed in this work.
HHO is a recently developed swarm-based stochastic algorithm that has previously shown …

This paper proposes a novel population-based optimization algorithm called Sine Cosine
Algorithm (SCA) for solving optimization problems. The SCA creates multiple initial random …

Abstract Particle Swarm Optimization (PSO) is one of the most widely used heuristic
algorithms. The simplicity and inexpensive computational cost makes this algorithm very …

In pedagogy, teachers usually separate mixed-level students into different levels, treat them
differently and teach them in accordance with their cognitive and learning abilities. Inspired …

Although several meta-heuristics have been developed in the last two decades, most of
them are population-based, undergo many steps along with several parameters that make …

Swarm intelligence is a research field that models the collective intelligence in swarms of
insects or animals. Many algorithms that simulates these models have been proposed in …