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 …

Differential evolution (DE) is one of the highly acknowledged population-based optimization
algorithms due to its simplicity, user-friendliness, resilience, and capacity to solve problems …

Continuous ant colony optimization was a population-based heuristic search algorithm
inspired by the pathfinding behavior of ant colonies with a simple structure and few control …

In this article, a new feature selection (FS) algorithm, called simple, fast, and efficient (SFE),
is proposed for high-dimensional datasets. The SFE algorithm performs its search process …

The development of technologies for the additive manufacturing, in particular of metallic
materials, is offering the possibility of producing parts with complex geometries. This opens …

The gaining sharing knowledge based optimization algorithm (GSK) is recently developed
metaheuristic algorithm, which is based on how humans acquire and share knowledge …

Over the last several years, DBSCAN (Density-Based Spatial Clustering of Applications with
Noise) has been widely applied in many areas of science due to its simplicity, robustness …

Particle swarm optimization (PSO) is a heuristic optimization algorithm generally applied to
continuous domains. Binary PSO is a form of PSO applied to binary domains but uses the …

In this paper, an efficient method for solving multiple knapsack problem (MKP) using discrete
differential evolution is proposed. Firstly, an integer programming model of MKP suitable for …

Computer systems store massive amounts of data with numerous features, leading to the
need to extract the most important features for better classification in a wide variety of …