Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms
in the literature. Although the original PSO has shown good optimization performance, it still …

This study develops a novel metaheuristic algorithm that is motivated by the behavior of
jellyfish in the ocean and is called artificial Jellyfish Search (JS) optimizer. The simulation of …

Particle swarm optimization (PSO) is one of the most well-regard metaheuristics with
remarkable performance when solving diverse optimization problems. However, PSO faces …

Particle swarm optimization (PSO) is one of the well-known population-based techniques
used in global optimization and many engineering problems. Despite its simplicity and …

A novel hybrid particle swarm and simulated annealing stochastic optimization method is
proposed. The proposed hybrid method uses both PSO and SA in sequence and integrates …

Particle swarm optimization is a stochastic population-based algorithm based on social
interaction of bird flocking or fish schooling. In this paper, a new adaptive inertia weight …

In a competitive market, it is of great significance to divide customer groups to develop
customer-centered personalized products. In this paper, we propose a customer …

This paper applies a new hybrid method by a combination of three population base
algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and …

Teaching–learning-based optimization (TLBO) is a recently proposed population-based
algorithm that simulates the process of teaching and learning. Compared with other …

Over the past two decades, large amounts of biomedical and clinical data have been
generated. These high dimensional datasets contain thousands of genes. However, such …