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 …

Exact optimization algorithms are not able to provide an appropriate solution in solving
optimization problems with a high-dimensional search space. In these problems, the search …

In this paper, we introduced a practical version of golden section search algorithm to
optimize multi/uni-modal objective functions. Accordingly, this study presented a novel …

In recent decades, many researchers have been interested in algorithms inspired by the
observation of natural phenomena to solve optimization problems. Among them, meta …

As a well-known stochastic optimization algorithm, the particle swarm optimization (PSO)
algorithm has attracted the attention of many researchers all over the world, which has …

Practical engineering optimization problems are almost constrained optimization problems
and difficult to be solved effectively, therefore, how to handle these problems has attracted …

The multi-level thresholding is a popular method for image segmentation. However, the
method is computationally expensive and suffers from premature convergence when level …

Meta-heuristic search algorithms are developed to solve optimization problems. Such
algorithms are appropriate for global searches because of their global exploration and local …

This study presents an adaptive two-layer particle swarm optimization algorithm with elitist
learning strategy (ATLPSO-ELS), which has better search capability than classical particle …

With the rapid advancements in the services computing paradigm, cloud computing has
been a fundamental requirement for enabling practically all sophisticated applications and …