Title :
Hybrid genetic algorithm based on cloud model in dynamic environment
Author :
Hao Chen ; Ming Li ; Xi Chen
Author_Institution :
Key Lab. of Nondestructive, Test (Minist. of Educ.), Nanchang Hangkong Univ., Nanchang, China
Abstract :
In recent years there is a growing interest in the research of applying genetic algorithms (GAs) for dynamic optimization problems (DOPs), and several approaches have developed to deal with DOPs. Cloud model is a model of transforming a qualitative concept to a set of quantitative numerical values. A new hybrid genetic algorithm based on cloud model is proposed in this paper, cloud model is used to enhance search in dynamic landscape and predetermine the conceivable moving direction of the optimum when the environment is changed. The computation results indicate that the new algorithm has the approving performance in dealing with the dynamic optimization problems.
Keywords :
genetic algorithms; DOP; GA; cloud model; conceivable moving direction; dynamic environment; dynamic landscape; dynamic optimization problems; genetic algorithms; hybrid genetic algorithm; quantitative numerical values; Computational modeling; Evolutionary computation; Generators; Genetic algorithms; Heuristic algorithms; Numerical models; Optimization; cloud model; dynamic optimization problems; hybrid genetic algorithm;
Conference_Titel :
Information and Automation (ICIA), 2013 IEEE International Conference on
Conference_Location :
Yinchuan
DOI :
10.1109/ICInfA.2013.6720315
