一种求解约束函数优化问题的遗传算法

遗传算子和种群更新策略在遗传算法全局寻优过程中发挥着重要作用，通过多父体杂交算子使产生的后代更具多样性和采用最小代数代沟种群替换模型有效地均衡算法对问题解空间的探索和开发能力提高算法的性能，给出了一种求解约束函数优化问题的遗传算法。对两个典型约束函数优化问题进行了数值实验，实验结果表明了该算法的有效性和稳健性。

A genetic algorithm for solving constrained function optimization problems

In this paper, a new genetic algorithm is presented to solve constrained function optimization problems. This algorithm can maintain the diversity of the population by using multi-parent crossover and can get high performance by employing minimal generation gap modal to balance the exploration and exploitation to the solution space of the problem effectively. Through the com- puter simulation on two benchmark constrained functions, the numerical experimental results show that this algorithm is effective and stable to solve constrained function optimization problems.