The Mixed Optimization Algorithm And Its Application In The Rolling Regulations Based On Evolution Computation

Genetic algorithm is a stochastic search algorithm which use for reference the natural select and the natural genetic of biology, since the professor Holland put forward the genetic algorithm in 60th, where have obtain a lot of important research fruit。in each scopes it has extensive application。Because the genetic algorithm's serviceability is good, robust, can solve the complex optimized problem which tradition search algorithm with difficulty or is unable soluted, already became a hot research area of intelligent optimization method。When genetic algorithm used in the high dimension complex question, the optimization easy to fall into the partial solution, optimized ability drops, searches for the overall situation optimal solution with difficulty。In order to enhance the ability that genetic algorithm to the complex optimized question solution, in the multianalysis foundation to the current genetic algorithm research newest progress, proposed the mixed optimization algorithm based on the evolutionary computation, further enhances the optimization ability associate genetic algorithm with other optimized algorithm to solve the high dimension complex question。Combine the peculiarity of the Agent and the ideal of evolutionary computation,we put forward the evolutional algorithm based on Multi-Agent which have obtained available effect on function optimization。According to the peculiarity of individual which consist in grid and the peculiarity of evolution operator,and combine with other optimize algorithm to put forward a new mixed optimize algorithm which made the capability of optimize more efficient。According to the peculiarity of evolution operator,we combine it with other optimize algorithm to put forward a new mixed optimize algorithm,and validate the capability of the mixed optimize algorithm through the experiment。The quantum algorithm is a novel evolution algorithm appeared recently, which adopt novel quantum coding and using full disturb cross and quantum mutation to search the best result of the problems, which have better searching capability than traditional genetic algorithm。This paper analyze the quantum code and the fashion of evolution。And combine with the traditional real number code, put forward the quantum genetic algorithm based on Multi-Agent and the mixed optimize algorithm which combine quantum evolution with simulation anneal。Simulate experiment show that the mixed algorithm is better than single algorithm。This paper use the MAGA to optimize the rolling rules on the foundation of experience method, obtain the rolling rules which made the overall energy consume minimum。The simulation results show that MAGA could find the better rolling rules more rapidly and more effective。Accomplish the accessorial intelligent optimize system of rolling rules。...