Particle swarm optimization: A comprehensive survey
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 …
in the literature. Although the original PSO has shown good optimization performance, it still …
[PDF][PDF] A review of population-based meta-heuristic algorithms
Z Beheshti, SMH Shamsuddin - Int. j. adv. soft comput. appl, 2013 - academia.edu
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 …
optimization problems with a high-dimensional search space. In these problems, the search …
A new optimization algorithm based on chaotic maps and golden section search method
JA Koupaei, SMM Hosseini, FMM Ghaini - Engineering Applications of …, 2016 - Elsevier
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 …
optimize multi/uni-modal objective functions. Accordingly, this study presented a novel …
Memetic binary particle swarm optimization for discrete optimization problems
In recent decades, many researchers have been interested in algorithms inspired by the
observation of natural phenomena to solve optimization problems. Among them, meta …
observation of natural phenomena to solve optimization problems. Among them, meta …
A novel improved particle swarm optimization algorithm based on individual difference evolution
J Gou, YX Lei, WP Guo, C Wang, YQ Cai, W Luo - Applied Soft Computing, 2017 - Elsevier
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 …
algorithm has attracted the attention of many researchers all over the world, which has …
An adaptive switchover hybrid particle swarm optimization algorithm with local search strategy for constrained optimization problems
Z Liu, Z Qin, P Zhu, H Li - Engineering Applications of Artificial Intelligence, 2020 - Elsevier
Practical engineering optimization problems are almost constrained optimization problems
and difficult to be solved effectively, therefore, how to handle these problems has attracted …
and difficult to be solved effectively, therefore, how to handle these problems has attracted …
A novel hybrid algorithm of gravitational search algorithm with genetic algorithm for multi-level thresholding
G Sun, A Zhang, Y Yao, Z Wang - Applied Soft Computing, 2016 - Elsevier
The multi-level thresholding is a popular method for image segmentation. However, the
method is computationally expensive and suffers from premature convergence when level …
method is computationally expensive and suffers from premature convergence when level …
CAPSO: centripetal accelerated particle swarm optimization
Z Beheshti, SMH Shamsuddin - Information Sciences, 2014 - Elsevier
Meta-heuristic search algorithms are developed to solve optimization problems. Such
algorithms are appropriate for global searches because of their global exploration and local …
algorithms are appropriate for global searches because of their global exploration and local …
An adaptive two-layer particle swarm optimization with elitist learning strategy
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 …
learning strategy (ATLPSO-ELS), which has better search capability than classical particle …
Towards energy efficient Smart city services: A software defined resource management scheme for data centers
With the rapid advancements in the services computing paradigm, cloud computing has
been a fundamental requirement for enabling practically all sophisticated applications and …
been a fundamental requirement for enabling practically all sophisticated applications and …