Abstract: Simulated annealing and multigroup parallel evolution are two helpful methods which can improve the performance of genetic algorithm.These two ideas are well combined in this paper, and a new algorithm is derived, that is the multigroup parallel genetic algorithm based on simulated annealing method.Simulation results show that this method not only quickens the computation, but also improves the convergence efficiency, thus produces more satisfactory results.
Based on Joines's research, a hybrid genetic algorithm based on Elitist strategy and Adaptive genetic algorithm is proposed considering the effect of different amount of every part.
Through redesigning cross operator and variation operator on classical genetic algorithm, a self adaptative genetic algorithm based on relay search method is proposed in this paper.
He has led many projects, including "Research on the theory and application of genetic algorithm-based water resources allocation" that is financed by the Young Doctor Foundation of Wuhan University, "Research on the AI-based water resource optimized allocation theory" by State Key Lab of Wuhan University in water resources and hydroelectricity engineering field.
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