Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
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.
Adaptively choosing niching parameters in a PSO
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Optimization using particle swarms with near neighbor interactions
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
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
Locating and tracking multiple dynamic optima by a particle swarm model using speciation
IEEE Transactions on Evolutionary Computation
A Particle Swarm Optimization Method for Multimodal Optimization Based on Electrostatic Interaction
MICAI '09 Proceedings of the 8th Mexican International Conference on Artificial Intelligence
Niching without niching parameters: particle swarm optimization using a ring topology
IEEE Transactions on Evolutionary Computation
A novel particle swarm niching technique based on extensive vector operations
Natural Computing: an international journal
Particle swarm optimization with gravitational interactions for multimodal and unimodal problems
MICAI'10 Proceedings of the 9th Mexican international conference on Artificial intelligence conference on Advances in soft computing: Part II
Genetic algorithms and particle swarm optimization for exploratory projection pursuit
Annals of Mathematics and Artificial Intelligence
Information Sciences: an International Journal
Niching particle swarm optimization with local search for multi-modal optimization
Information Sciences: an International Journal
Gravitational interactions optimization
LION'05 Proceedings of the 5th international conference on Learning and Intelligent Optimization
SEMCCO'11 Proceedings of the Second international conference on Swarm, Evolutionary, and Memetic Computing - Volume Part I
Memetic fitness euclidean-distance particle swarm optimization for multi-modal optimization
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
| Hi-index | 0.00 |
One of the most critical issues that remains to be fully addressed in existing multimodal evolutionary algorithms is the difficulty in pre-specifying parameters used for estimating how far apart optima are. These parameters are typically represented as some sorts of niching parameters in existing EAs. Without prior knowledge of a problem, it is almost impossible to determine appropriate values for such niching parameters. This paper proposes a PSO for multimodal optimization that removes the need of these niching parameters. Our results show that the proposed algorithm, Fitness Euclidean-distance Ratio based PSO (FER-PSO) is able to reliably locate multiple global optima on the search landscape over some widely used multimodal optimization test functions, given that the population size is sufficiently large.