关键词: 全局最优, 非线性约束优化, 差分进化, 混沌

Abstract: This paper presents an improved adaptive differential evolution algorithm for the nonlinear constrained optimization problems.In this algorithm，the fixed weighting factor and crossover probability factor of the differential evolution are improved.The constrained optimization problems are converted into unconstrained bi-objective optimization problem by the definition of the constraint violation function.In each iteration，keeping a part of the performance of better infeasible particles is to maintain the diversity of the swarm.Mutation operator is introduced to expand the search range of the particle.Numerical experiments show that the proposed algorithm has faster convergence speed and better ability of global optimization.

Key words: global optimal, nonlinear constrained optimization, differential evolution, chaotic