Since its inception in 1995, Differential Evolution (DE) has emerged as one of the most
frequently used algorithms for solving complex optimization problems. Its flexibility and …

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

The novelty of this article lies in introducing a novel stochastic technique named the
Hippopotamus Optimization (HO) algorithm. The HO is conceived by drawing inspiration …

Abstract Grey Wolf Optimizer (GWO) is a new swarm intelligence algorithm mimicking the
behaviours of grey wolves. Its abilities include fast convergence, simplicity and easy …

Differential Evolution (DE) is arguably one of the most powerful and versatile evolutionary
optimizers for the continuous parameter spaces in recent times. Almost 5 years have passed …

Artificial bee colony (ABC) and its most modifications use a probability method to select
good food sources (called solutions) in the onlooker bee search phase. However, the …

This paper proposes a facial expression recognition system using evolutionary particle
swarm optimization (PSO)-based feature optimization. The system first employs modified …

This paper proposes a novel optimization method for solving real-world optimization
problems. It is inspired by a cooperative human phenomenon named the mountaineering …

Differential evolution (DE) is a simple yet powerful evolutionary algorithm for numerical
optimization. However, the performance of DE significantly relies on its mutation operator …

Differential evolution (DE) is a well-known evolutionary algorithm with simple operation and
excellent performance, which has been applied to solve various optimization problems. To …