Reducing bias and inefficiency in the selection algorithm
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Hybrid fuzzy-genetic technique for multisensor fusion
Information Sciences: an International Journal
A Cooperative Coevolutionary Approach to Function Optimization
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Constraint handling in genetic algorithms using a gradient-based repair method
Computers and Operations Research
Predictive models for the breeder genetic algorithm i. continuous parameter optimization
Evolutionary Computation
Classification Techniques of Neural Networks Using Improved Genetic Algorithms
WGEC '08 Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing
A hybrid search algorithm with heuristics for resource allocation problem
Information Sciences: an International Journal
Gradual distributed real-coded genetic algorithms
IEEE Transactions on Evolutionary Computation
A hybrid evolutionary imperialist competitive algorithm (HEICA)
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part I
Applied Soft Computing
Hi-index | 12.05 |
This paper proposes a hybrid approach by combining the evolutionary optimization based genetic algorithm (GA) and socio-political process based colonial competitive algorithm (CCA). The performance of hybrid algorithm is illustrated using standard test functions in comparison to basic CCA method. Since the CCA method is newly developed, very little research work has been undertaken to deal with curse of dimensionality and to improve the convergence speed and accuracy of the basic CCA algorithm. The proposed CCA-GA algorithm is then used to tune a PID controller for a real time ball and beam system. Simulation results were reported and the hybrid algorithm indeed has established superiority over the basic algorithms with respect to set of functions considered and it can easily be extended for other global optimization problems.