求解约束优化问题的退火遗传算法

针对基于罚函数遗传算法求解实际约束优化问题的困难与缺点，提出了求解约束优化问题的退火遗传算法。对种群中的个体定义了不可行度，并设计退火遗传选择操作。算法分三阶段进行，首先用退火算法搜索产生初始种群体，随后利用遗传算法使搜索逐渐收敛于可行的全局最优解或较优解，最后用退火优化算法对解进行局部优化。两个典型的仿真例子计算结果证明该算法能极大地提高计算稳定性和精度。

Annealing-Genetic Algorithm for Constrained Optimization Problems

Taking into consideration of the difficulty and disadvantage of genetic algorithms based on the penalty function methods to handle the constrained optimization problems, an annealing genetic algorithm for constrained optimization problems is proposed for constrained optimization problems. The method is divided into three phases: enough initial feasible solution is produced by using simulated annealing, the GA is applied to search for the feasible optimum solution, and annealing algorithm is proposed to optimize optimum solution. The simulation results for two numerical examples show the well performance of the presented algorithm.