求解全局优化问题的遗传退火算法  

Genetic-annealing algorithm for global optimization problems

作　　者：邵平凡[1] 万程鹏[1] 

机构地区：[1]武汉科技大学计算机学院,武汉430081

出　　处：《计算机工程与应用》2007年第12期62-65,共4页Computer Engineering and Applications

摘　　要：针对全局优化过程中,算法计算时间长、收敛时机不成熟、容易陷入局部最优等现象,在分析模拟退火算法和遗传算法优缺点的基础上提出了新的遗传退火混合算法,并将新的交叉、变异策略和诱导微调方法应用于算法中,通过10组非线性约束函数的测试表明,该算法能够在保持较高精度的前提下快速收敛。Based on the analyzing of the simulate annealing algorithm and genetic algorithm,a genetic-annealing algorithm with new crossover strategy,mutation strategy and inducing adjustment strategy is proposed to solve the problems including taking long time,premature convergence,and easily trapping into local optimum value in the process of global optimization.This paper adopts ten typical test functions to experiment.The results demonstrate that the algorithm can converge quickly with high accuracy.

关 键 词：全局优化 遗传退火算法 交叉策略 变异策略 诱导微调 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]