An improved genetic algorithm(GA) with particle swarm’s evolutionary(IGA PSE) strategy is proposed to solve
constrained optimization problems(COP). Firstly, the relation and its characters between the statistics information of the degree of constraint deviation and the constraint violation functions of candidate solutions are analyzed, and an improved constraint handling method is proposed by using statistics information of the degree of constraint condition deviation. Secondly, three novel mutation operators with particle swarm’s evolutionary strategy are applied to IGA PSE. Then, three situations of premature convergence are argued, and the corresponding strategy of diversity maintenance is proposed. Finally, numerical experiments of standard test functions show that the proposed method can solve the constraint optimization problems effectively.