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.)
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Adaptive Selection Methods for Genetic Algorithms
Proceedings of the 1st International Conference on Genetic Algorithms
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Multiobjective evolutionary algorithms: classifications, analyses, and new innovations
Hybrid Evolutionary Algorithm Based on PSO and GA Mutation
HIS '06 Proceedings of the Sixth International Conference on Hybrid Intelligent Systems
A hybrid of genetic algorithm and particle swarm optimization for recurrent network design
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Research frontier: memetic computation-past, present & future
IEEE Computational Intelligence Magazine
Application notes: memetic mission management
IEEE Computational Intelligence Magazine
Towards a memetic feature selection paradigm
IEEE Computational Intelligence Magazine
Memetic compact differential evolution for cartesian robot control
IEEE Computational Intelligence Magazine
Natural and remote sensing image segmentation using memetic computing
IEEE Computational Intelligence Magazine
Hybrid approaches and dimensionality reduction for portfolio selection with cardinality constraints
IEEE Computational Intelligence Magazine
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
An investigation into the merger of stochastic diffusion search and particle swarm optimisation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A new multi-swarm multi-objective particle swarm optimization based on pareto front set
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
A new iterative mutually coupled hybrid GA-PSO approach for curve fitting in manufacturing
Applied Soft Computing
Dynamic index tracking via multi-objective evolutionary algorithm
Applied Soft Computing
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A sophisticated GA/PSO-hybrid algorithm for application to real-world optimization problems was proposed. The configurations of the two consisting methods, GA and PSO, were investigated to enhance the diversity of the former and the fast convergence of the latter simultaneously. The new hybrid algorithm was applied to two test function problems, and the results indicated that the search ability was improved by suitable tuning of the configurations. In addition, the new hybrid algorithm showed robust search ability regardless of the selection of the initial population. The new hybrid algorithm was also applied to a diesel engine combustion chamber design problem. The obtained non-dominated solutions have a variety in their configurations. Several solutions that dominate the baseline configuration were successfully found within a few generations, and the trade-off relation between soot reduction and diffusion combustion period was also determined. In addition, useful design information was obtained by investigating the optimization results; the length from the center of the combustion chamber to the lip is the control design variable of trade-off between the soot reduction and diffusion combustion period, and the large width of the center of the combustion chamber improves soot emission and diffusion combustion period at the same time.