关键词: 动态优化, 非线性约束优化, 进化算法, 熵函数

Abstract: Dynamic nonlinear constrainted optimization is a class of complex dynamic optimization problems，the difficult to solve the dynamic nonlinear constrainted optimization problem is how to do with the constraint and the time（invironment） variance.In this paper，a new method for solving a class of nonlinear constrained optimization problem defined in discrete time（environment） space is given.A new dynamic entropy function based on the constraint conditions of dynamic nonlinear constrainted optimization problem is given.Using the new entropy function，the orignal optimization problem is transformed into a bi-objective dynamic optimization problem.A new crossover operator and a mutation operator with local search are designed.Based on these，a new multiobjective optimization envolutionary algorithm is proposed.The computer simulations are made on two dynamic nonlinear constrained optimization problems，and the results indicate the proposed algorithm is effective.

Key words: dynamic optimization, nonlinear constrained optimization, evolutionary algorithm, entropy fuction