Metaheuristic Optimization Algorithms Research
This cluster of papers focuses on swarm intelligence optimization algorithms, including Particle Swarm Optimization, Differential Evolution, Ant Colony Optimization, and Firefly Algorithm. These nature-inspired metaheuristic algorithms are used for global optimization and have applications in various fields.
Papers listed on taxonomy pages are the top few works per node from the OpenAlex snapshot. That list is not exhaustive and is not an endorsement. The topic map and the journal registry remain separate: there is still no authoritative topic-to-venue or topic-to-organization edge. Search is a lexical lookup, not a claim that a venue publishes a topic.
Most cited
- Particle swarm optimization
- Grey Wolf Optimizer
- The Whale Optimization Algorithm
- No free lunch theorems for optimization
- Ant system: optimization by a colony of cooperating agents
- The particle swarm - explosion, stability, and convergence in a multidimensional complex space
Most recent
- Empirical analysis of algorithmic components for improved performance in a baseline genetic algorithm selection hyper-heuristic
- Termite thermoregulation optimization (TTO): an HPC-oriented nature-inspired metaheuristic for global optimization
- MSE-CDO: A Multi-Strategy Enhanced Cloud Drift Optimizer for Global and Constrained Engineering Optimization
- Weather State Ants Optimizer: A Markov-Driven Variable-Structure Metaheuristic
- Evaluating the Solution Performance of the Augmented Lagrangian Function on Ising Machines
- APPROACH-AVOIDANCE OPTIMIZATION ALGORITHM: A NOVEL METAPHOR-FREE OPTIMIZER WITH APPLICATIONS IN DATA CLUSTERING