Opposition-based Learning (OBL) is a new concept in machine learning, inspired from the
opposite relationship among entities. In 2005, for the first time the concept of opposition was …

Metaheuristic algorithms are widely used in various fields of optimization engineering.
These algorithms have become popular because of their ability to explore and exploit …

To help individuals or companies make a systematic and more accurate decisions,
sentiment analysis (SA) is used to evaluate the polarity of reviews. In SA, feature selection …

Metaheuristic algorithms are extensively recognized as effective approaches for solving high-
dimensional optimization problems. These algorithms provide effective tools with important …

This paper introduces a new meta-heuristic technique, named geometric mean optimizer
(GMO) that emulates the unique properties of the geometric mean operator in mathematics …

Building highly accurate model for solar cells and photovoltaic (PV) modules based on
experimental data is vital for the simulation, evaluation, control, and optimization of PV …

Particle swarm optimization (PSO) has been shown to yield good performance for solving
various optimization problems. However, it tends to suffer from premature convergence …

Abstract Salp Swarm Algorithm (SSA) is a recent approach with a simple implementation,
few parameters, and low computational cost. SSA has been used in different optimization …

Diverse forms of opposition are already existent virtually everywhere around us, and utilizing
opposite numbers to accelerate an optimization method is a new idea. Since 2005 …

This paper presents a novel algorithm based on generalized opposition-based learning
(GOBL) to improve the performance of differential evolution (DE) to solve high-dimensional …