一种遗传算法求约束优化问题的新方法

New method in solving constrained optimization with GA

为了更好的解决约束优化问题,介绍了利用遗传算法求解约束优化问题的一般方法,在分析传统方法的基础上提一种遗传算法求解约束优化问题的新方法,将约束优化问题分成两步:首先不考虑目标函数,把约束优化问题转换为一个约束满足问题来处理,获得一个可行解;然后对目标函数和已满足约束的条件进行优化,最终获得一个最优解。还对该方法在不同问题下作了分析,证明了该方法对求解有约束优化问题有良好性能。

In order to solve the constrained optimization problems effectively, we analyzed traditional methods and propose a new method to solve the problems using genetic algorithms. We divide the constrained the optimization into two steps. In the first step, the objective function is completely disregarded and the constrained optimization problem is treated as a constraint satisfaction problem. In the second step, we perform the constrain optimization and got the optimized solution finally. We analyze the proposed method in different problems and demonstrate the proposed method performs well in solving the constrained optimization problems.