Particle swarm optimization for nonlinear complementarity problems
Jianke Zhang · Computer Engineering and Applications Journal · 2009
According to a class of nonlinear complementarity problems,a new algorithm is proposed;this algorithm combines Par- ticle Swarm Optimization with maximum entropy function method.Firstly,the maximum entropy function is used to transform the nonlinear complementarity problems into unconstrained optimization problems,this function is used as Particle Swarm Optimiza-tion’s fitness function;Then Particle Swarm Optimization is applied to solving the unconstrained optimization problems.The numerical results show that the algorithm converges faster,numerical stability,and it is an effective algorithm for complementarity minimax problems.