Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Swarm intelligence
Dynamic Search With Charged Swarms
GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
An Empirical Comparison of Particle Swarm and Predator Prey Optimisation
AICS '02 Proceedings of the 13th Irish International Conference on Artificial Intelligence and Cognitive Science
Ant Colony Optimization
Learning and Measuring Specialization in Collaborative Swarm Systems
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Center particle swarm optimization
Neurocomputing
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
EPSO - best-of-two-worlds meta-heuristic applied to power system problems
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Extending particle swarm optimisers with self-organized criticality
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Convergence behavior of the fully informed particle swarm optimization algorithm
Proceedings of the 10th annual conference on Genetic and evolutionary computation
An evolutionary game-theoretical approach to particle swarm optimisation
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
Neighborhood re-structuring in particle swarm optimization
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Neighborhood topologies in fully informed and best-of-neighborhood particle swarms
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
A hierarchical particle swarm optimizer and its adaptive variant
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Frankenstein's PSO: a composite particle swarm optimization algorithm
IEEE Transactions on Evolutionary Computation
Heterogeneous particle swarm optimization
ANTS'10 Proceedings of the 7th international conference on Swarm intelligence
Adaptive fuzzy particle swarm optimization for global optimization of multimodal functions
Information Sciences: an International Journal
Information Sciences: an International Journal
An heterogeneous particle swarm optimizer with predator and scout particles
AIS'12 Proceedings of the Third international conference on Autonomous and Intelligent Systems
A self-adaptive heterogeneous PSO inspired by ants
ANTS'12 Proceedings of the 8th international conference on Swarm Intelligence
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Particle swarm optimization (PSO) is a swarm intelligence technique originally inspired by models of flocking and of social influence that assumed homogeneous individuals. During its evolution to become a practical optimization tool, some heterogeneous variants have been proposed. However, heterogeneity in PSO algorithms has never been explicitly studied and some of its potential effects have therefore been overlooked. In this paper, we identify some of the most relevant types of heterogeneity that can be ascribed to particle swarms. A number of particle swarms are classified according to the type of heterogeneity they exhibit, which allows us to identify some gaps in current knowledge about heterogeneity in PSO algorithms. Motivated by these observations, we carry out an experimental study of two heterogeneous particle swarms each of which is composed of two kinds of particles. Directions for future developments on heterogeneous particle swarms are outlined.