关键词: 粒子群算法, 进化算法, 极小极大问题, 邻近点算法

Abstract: Aiming at the discrete nonlinear minimax problems with each component being convex function, this paper proposes a particle swarm optimization-proximal point algorithm with global convergence. This algorithm changes the minimax problem to the unconstrained optimization problem of smooth function by maximum entropy function. It uses the proximal point algorithm as the outer algorithm, and the particle swarm optimization as the internal algorithm. The numerical results show that this algorithm has the advantage of the fine stability, fast convergence speed and high precision, and it is an effective algorithm for nonlinear minimax problems.

Key words: Particle Swarm Optimization（PSO）, evolutionary computation, minimax problems, proximal point algorithm