Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has
gained prominence in the last two decades due to its ease of application in unsupervised …
gained prominence in the last two decades due to its ease of application in unsupervised …
[HTML][HTML] Emperor penguin optimizer: A comprehensive review based on state-of-the-art meta-heuristic algorithms
Meta heuristics is an optimization approach that works as an intelligent technique to solve
optimization problems. Evolutionary algorithms, human-based algorithms, physics-based …
optimization problems. Evolutionary algorithms, human-based algorithms, physics-based …
INFO: An efficient optimization algorithm based on weighted mean of vectors
This study presents the analysis and principle of an innovative optimizer named weIghted
meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean …
meaN oF vectOrs (INFO) to optimize different problems. INFO is a modified weight mean …
Parameter adaptation-based ant colony optimization with dynamic hybrid mechanism
X Zhou, H Ma, J Gu, H Chen, W Deng - Engineering Applications of …, 2022 - Elsevier
In this paper, a parameter adaptation-based ant colony optimization (ACO) algorithm based
on particle swarm optimization (PSO) algorithm with the global optimization ability, fuzzy …
on particle swarm optimization (PSO) algorithm with the global optimization ability, fuzzy …
Boosted kernel search: Framework, analysis and case studies on the economic emission dispatch problem
R Dong, H Chen, AA Heidari, H Turabieh… - Knowledge-Based …, 2021 - Elsevier
In recent years, a variety of meta-heuristic nature-inspired algorithms have been proposed to
solve complex optimization problems. However, these algorithms suffer from the …
solve complex optimization problems. However, these algorithms suffer from the …
Ant colony optimization for traveling salesman problem based on parameters optimization
Y Wang, Z Han - Applied Soft Computing, 2021 - Elsevier
Traveling salesman problem (TSP) is one typical combinatorial optimization problem. Ant
colony optimization (ACO) is useful for solving discrete optimization problems whereas the …
colony optimization (ACO) is useful for solving discrete optimization problems whereas the …
An efficient modified grey wolf optimizer with Lévy flight for optimization tasks
AA Heidari, P Pahlavani - Applied Soft Computing, 2017 - Elsevier
The grey wolf optimizer (GWO) is a new efficient population-based optimizer. The GWO
algorithm can reveal an efficient performance compared to other well-established …
algorithm can reveal an efficient performance compared to other well-established …
Information-theory-based nondominated sorting ant colony optimization for multiobjective feature selection in classification
Feature selection (FS) has received significant attention since the use of a well-selected
subset of features may achieve better classification performance than that of full features in …
subset of features may achieve better classification performance than that of full features in …
A novel collaborative optimization algorithm in solving complex optimization problems
W Deng, H Zhao, L Zou, G Li, X Yang, D Wu - Soft Computing, 2017 - Springer
To overcome the deficiencies of weak local search ability in genetic algorithms (GA) and
slow global convergence speed in ant colony optimization (ACO) algorithm in solving …
slow global convergence speed in ant colony optimization (ACO) algorithm in solving …
An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems
Bat algorithm is a population metaheuristic proposed in 2010 which is based on the
echolocation or bio-sonar characteristics of microbats. Since its first implementation, the bat …
echolocation or bio-sonar characteristics of microbats. Since its first implementation, the bat …