Intelligent Evolutionary Algorithm for Fuzzy Programming Based on Nonlinear Support Vector Machine
نویسنده
چکیده
When the standard genetic algorithm is used to solve the fuzzy programming problem, poor convergence occurs. In order to overcome this defect, this paper presents a hybrid intelligent evolutionary algorithm based on nonlinear support vector machine (SVM) to solve the fuzzy programming problem. Firstly, based on the research of genetic algorithm, evolutionary strategy and genetic algorithm are combined together, and the idea of simulated annealing is introduced. Secondly, evolutionary strategy is used to improve evolution operator and selection operator. Thirdly, simulated annealing is used to improve the mutation operator. And the accuracy of the solution is improved. Finally, the fuzzy programming model based on the improved intelligent evolutionary algorithm is fitted and optimized by nonlinear support vector machine. Simulations show that the hybrid algorithm based on the support vector machine has higher convergence and can be applied to the fuzzy programming problems.
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