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《Acta Scientiarum Naturalium Universitatis Sunyatseni》 2011-01
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Solving Nonlinear Equations Based on Improved Genetic Algorithm

YAN Lewei1,CHEN Shuhui2(1.Department of Engineering Mechanics,Guangzhou University,Guangzhou 510006,China;2.Department of Applied Mechanics and Engineering,School of Engineering,Sun Yat-sen University,Guangzhou 510275,China)  
Some methods such as population isolation mechanism,optimum reserved strategy,arithmetic crossover,adaptive random mutation and heterogeneous strategy are used to improve genetic algorithm.Besides the advantage that the optimal solution can be found only by the value of objective function,the local searching capability is enhanced in this improve genetic algorithm.This algorithm is applied to solve nonlinear equations.Numerical examples demonstrated that this algorithm can solve the optimization problem which has nonlinear equality constraint.Furthermore,the heterogeneous strategy speeds up the process of convergence and raises the convergence probability of global optimal solution.
【Fund】: 国家自然科学基金资助项目(10972240)
【CateGory Index】: TP18;O241.7
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