A Novel Self-adaptive Behavior Quantum Evolutionary Algorithm
Hassan K. Khalafi · 2010
In accordance with tradition quantum evolutionary algorithms can obtain excellent results in the optimization of Multi-peak functions. In any case, they are easy to be trapped to hurriedness. In this article, A Novel Self-adaptive Behavior Quantum Evolutionary Algorithm is recommending on the basis of the concepts and tenet of quantum evolutionary algorithms in order to enhance the efficiency. Firstly, Self-adaptive Behavior triploid chromosome is constructed to keep the population variety; Secondly, double mutation is used to make sure the variety of the swarm, then individual chromosome cross will be imported into this new algorithm in order to achieve the information communication between the chromosomes and enlarge the search scope in the available space. Experiments on test functions of varied intricacies are implemented and compared with other EAs. The result indicates that the new algorithm in this article can search and get the global most efficient solution in a shorter time. (Hassan K. Khalafi. A Novel Self-adaptive Behavior Quantum Evolutionary Algorithm. Journal of American Science 2010;6(12):1483-1486). (ISSN: 1545-1003). http://www.americanscience.org.