%0 Journal Article
%T The Application of Genetic Algorithm in Solving Nonsmooth Optimization Problems
%A LONG Qiang
%J Journal of Chongqing Normal University
%D 2013
%I Chongqing Normal University
%X This paper considers an application of genetic algorithm in solving nonsmooth optimization problems.Nonsmooth optimization devote itself to solve programming problems whose objective function are continuous nondifferentiable.Since the objective function is nondifferentiable£¬the classical deterministic methods based on gradient may confront numerical difficulties.Therefore£¬it would be a good choice to use genetic algorithm£¬in which just information of objective function value but not information of gradient is needed£¬to solve nonsmooth optimization problems.Genetic algorithm is a stochastic method based on the evolutionary process of nature.It firstly codes the original optimization problem by means of binary encoding£¬Gary encoding or real number encoding.And then the next population generation is generated by applying crossover operator£¬mutation operator and selection operator.When the iteration time approach a sufficiently large number£¬the best chromosome in the current population will converge to the optimal solution or approximately optimal solution of the original problem.The genetic algorithm proposed in this paper uses real£­number encoding£¬arithmetic crossover£¬nonuniform mutation.And it selects the best population size of individuals in the selection step.Some minimax problems£¬which are nonsmooth optimization problems£¬are tested and their results are compared with some deterministic nonsmooth optimization methods.
%K genetic algorithm£»minimax problem£»nonsmooth optimization problem
%U http://journal.cqnu.edu.cn/1301/pdf/130103.pdf