基于遗传算法求解约束优化问题的一种算法

在用遗传算法求解约束优化问题时,处理好约束条件是取得好的优化效果的关键.通过考虑遗传算法和约束优化问题的某些特点,提出将直接比较方法和在进化群体中自适应地保持不可行解比例的策略相结合来处理约束条件的一种新方法,并将该方法结合到通用的遗传算法中.数值实验显示了这种方法的有效性.

A GA-Based Method for Solving Constrained Optimization Problems

In trying to solve constrained optimization problems using genetic algorithms, the method to handle the constraints is the key factor to success. In this paper, some features of GA (genetic algorithms) and a large class of constrained optimization problems are taken into account and a new method called Fixed Proportion and Direct Comparison (FPDC) is proposed, which combines direct comparison method and the strategy to keep a fixed proportion of infeasible individuals. It has been successfully integrated with the ordinary GA. Numerical results show that it is a general, effective and robust method.