Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Swarm intelligence
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
A note on the empirical evaluation of intermediate recombination
Evolutionary Computation
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
A TDMA scheduling scheme for many-to-one communications in wireless sensor networks
Computer Communications
Stochastic training of a biologically plausible spino-neuromuscular system model
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Handling Dynamic Networks Using Evolution in Ant-Colony Optimization
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
University course timetable planning using hybrid particle swarm optimization
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
A Multi-swarm Approach to Multi-objective Flexible Job-shop Scheduling Problems
Fundamenta Informaticae - Swarm Intelligence
An integrated framework of hybrid evolutionary computations
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Particle swarm optimization driven by evolving elite group
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Research frontier: the evolution of swarm grammars-growing trees, crafting art, and bottom-up design
IEEE Computational Intelligence Magazine
Strength pareto particle swarm optimization and hybrid ea-pso for multi-objective optimization
Evolutionary Computation
Engineering Applications of Artificial Intelligence
Information Sciences: an International Journal
Chaotic hybrid algorithm and its application in circle detection
EvoApplicatons'10 Proceedings of the 2010 international conference on Applications of Evolutionary Computation - Volume Part I
Hybrid particle swarm and conjugate gradient optimization algorithm
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
Evolving gene regulatory networks: a sensitivity-based approach
ICIC'11 Proceedings of the 7th international conference on Intelligent Computing: bio-inspired computing and applications
An opposition-based chaotic GA/PSO hybrid algorithm and its application in circle detection
Computers & Mathematics with Applications
A Multi-swarm Approach to Multi-objective Flexible Job-shop Scheduling Problems
Fundamenta Informaticae - Swarm Intelligence
A new iterative mutually coupled hybrid GA-PSO approach for curve fitting in manufacturing
Applied Soft Computing
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In this paper we propose a novel hybrid (GA/PSO) algorithm, Breeding Swarms, combining the strengths of particle swarm optimization with genetic algorithms. The hybrid algorithm combines the standard velocity and position update rules of PSOs with the ideas of selection, crossover and mutation from GAs. We propose a new crossover operator, Velocity Propelled Averaged Crossover (VPAC), incorporating the PSO velocity vector. The VPAC crossover operator actively disperses the population preventing premature convergence. We compare the hybrid algorithm to both the standard GA and PSO models in evolving solutions to five standard function minimization problems. Results show the algorithm to be highly competitive, often outperforming both the GA and PSO.