关键词: 粒子群算法, 进化算法, l-1模极小化问题, 极大熵函数

Abstract: According to a class of nonlinear l-1 norm minimization problems，a new hybrid algorithm is proposed to combine particle swarm optimization with maximum entropy function method.Firstly，the maximum entropy function is used to transform nonlinear l-1 norm minimization problems into a smooth function of unconstrained optimization problems，this smooth function is used as particle swarm optimization’s fitness function；Then particle swarm optimization is used to optimize the problems.The numerical results show that the algorithm converges faster，numerical stability，and it is an effective algorithm for nonlinear l-1 norm minimization problems.

Key words: Particle Swarm Optimization, evolutionary computation, l-1 norm minimization Problem, maximum entropy method