Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Niching methods for genetic algorithms
Niching methods for genetic algorithms
GAS, a concept on modeling species in genetic algorithms
Artificial Intelligence
Swarm intelligence
A species conserving genetic algorithm for multimodal function optimization
Evolutionary Computation
An Investigation of Niche and Species Formation in Genetic Function Optimization
Proceedings of the 3rd International Conference on Genetic Algorithms
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
An analysis of the behavior of a class of genetic adaptive systems.
An analysis of the behavior of a class of genetic adaptive systems.
Experimental study of speciation in ecological niche theory using genetic algorithms
Experimental study of speciation in ecological niche theory using genetic algorithms
Adaptively choosing niching parameters in a PSO
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Rotated test problems for assessing the performance of multi-objective optimization algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Comparison of multi-modal optimization algorithms based on evolutionary algorithms
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Fundamentals of Computational Swarm Intelligence
Fundamentals of Computational Swarm Intelligence
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
A multimodal particle swarm optimizer based on fitness Euclidean-distance ratio
Proceedings of the 9th annual conference on Genetic and evolutionary computation
A sequential niche technique for multimodal function optimization
Evolutionary Computation
Niche radius adaptation in the CMA-ES niching algorithm
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Fitness sharing and niching methods revisited
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
On the computation of all global minimizers through particle swarm optimization
IEEE Transactions on Evolutionary Computation
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
Erratum to "Niching without Niching parameters: particle swarm optimization using a ring topology"
IEEE Transactions on Evolutionary Computation
A bi-criterion approach to multimodal optimization: self-adaptive approach
SEAL'10 Proceedings of the 8th international conference on Simulated evolution and learning
Cellular particle swarm optimization
Information Sciences: an International Journal
Information Sciences: an International Journal
An automatic niching particle swarm for multimodal function optimization
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Niching particle swarm optimization with local search for multi-modal optimization
Information Sciences: an International Journal
Evolutionary multimodal optimization using the principle of locality
Information Sciences: an International Journal
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
WCCI'12 Proceedings of the 2012 World Congress conference on Advances in Computational Intelligence
Ensemble of clearing differential evolution for multi-modal optimization
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
A selective teaching-learning based niching technique with local diversification strategy
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
Clustered parent centric normal cross-over for multimodal optimization
SEMCCO'12 Proceedings of the Third international conference on Swarm, Evolutionary, and Memetic Computing
A dynamic archive based niching particle swarm optimizer using a small population size
ACSC '11 Proceedings of the Thirty-Fourth Australasian Computer Science Conference - Volume 113
High dimensional problem based on elite-grouped adaptive particle swarm optimization
ICIC'13 Proceedings of the 9th international conference on Intelligent Computing Theories and Technology
Quadratic interpolation based orthogonal learning particle swarm optimization algorithm
Natural Computing: an international journal
Accurate sub-swarms particle swarm optimization algorithm for service composition
Journal of Systems and Software
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Niching is an important technique for multimodal optimization. Most existing niching methods require specification of certain niching parameters in order to perform well. These niching parameters, often used to inform a niching algorithm how far apart between two closest optima or the number of optima in the search space, are typically difficult to set as they are problem dependent. This paper describes a simple yet effective niching algorithm, a particle swarm optimization (PSO) algorithm using a ring neighborhood topology, which does not require any niching parameters. A PSO algorithm using the ring topology can operate as a niching algorithm by using individual particles' local memories to form a stable network retaining the best positions found so far, while these particles explore the search space more broadly. Given a reasonably large population uniformly distributed in the search space, PSO algorithms using the ring topology are able to form stable niches across different local neighborhoods, eventually locating multiple global/local optima. The complexity of these niching algorithms is only O(N), where N is the population size. Experimental results suggest that PSO algorithms using the ring topology are able to provide superior and more consistent performance over some existing PSO niching algorithms that require niching parameters.