求解全局优化问题的智能遗传算法
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摘要
提出了一种智能遗传算法,该算法融合了5种交叉算子、8种变异算子和5种灾变算子,能根据当前优化结果智能地选择交叉算子、变异算子和灾变算子,在不影响搜索过程随机性的前提下收敛于全局最优解。不同于传统遗传算法,本算法增加了对各种算子优化性能的统计,在优化过程中尽可能使用那些优化性能高的算子,从而提高了智能遗传算法的优化性能。为了验证本算法的性能,采用12种传统遗传算法和本算法同时对20个测试函数进行了求解。最终的数据实例表明,方法是可行的、正确的和有效的。
Intelligent Genetic Algorithm(IGA)was proposed for solving global optimization problem.Five cross operators,eight mutation operators and five rebound operators were joined into IGA.This algorithm selects the appropriate cross operator,mutation operator and rebound operator according to the current optimization results,and converges the global optimization solution without the influence of random search process.Other than traditional GA,IGA increased statistical function to the optimization performance of these operators and applied the appropriate operator with best performance to advance optimization process.In order to validate the performance of this algorithm,20 testing functions were solved by IGA and other 12 traditional genetic algorithms.Numerous examples suggest that the algorithm is feasible,correct and valid.
Intelligent Genetic Algorithm(IGA)was proposed for solving global optimization problem.Five cross operators,eight mutation operators and five rebound operators were joined into IGA.This algorithm selects the appropriate cross operator,mutation operator and rebound operator according to the current optimization results,and converges the global optimization solution without the influence of random search process.Other than traditional GA,IGA increased statistical function to the optimization performance of these operators and applied the appropriate operator with best performance to advance optimization process.In order to validate the performance of this algorithm,20 testing functions were solved by IGA and other 12 traditional genetic algorithms.Numerous examples suggest that the algorithm is feasible,correct and valid.
引文
[1]金聪.函数优化中实数型遗传算法的研究[J].小型微型计算机系统.2000,21(4):372-374.
[2]孙艳丰,王众托.遗传算法在优化问题中的应用研究进展[J].控制与决策.1996,11(4):425-431.
[3]蓝海,王雄,王凌.复杂函数全局最优化的改进遗传退火算法[J].清华大学学报(自然科学版).2002,42(9):1237-1240.
[4]郭立新,武丽梅,李庆忠,等.一种基于多峰值多规则并行搜索的遗传算法[J].机械科学与技术.1999,18(3):406-411.
[5]Yiu-Wing Leung,Yuping Wang.An orthogonal genetic algorithm with quantization for global numerical optimization[J].IEEE transaction on evolutionary computation(S1089-778X).2001,5(1):41-53.
[6]李绍军,王惠,姚平经.求解全局最优化的遗传(GA)-Alopex算法的研究[J].信息与控制.2000,29(4):304-314.
[7]孟红云,刘三阳.基于免疫的多峰极值遗传算法[J].系统工程与电子技术.2003,25(4):477-512.
[8]韩炜,廖振鹏.一种全局优化算法:遗传算法----单纯型法[J].地震工程与工程振动.2001,21(2):6-12.
[9]雷德明.利用混沌搜索全局最优解的一种混合遗传算法[J].系统工程与电子技术.1999,21(12):80-81.
[10]谢巍,方康玲.一种求解不可微非线性函数的全局解的混合遗传算法[J].控制理论与应用.2000,17(2):180-183.
[2]孙艳丰,王众托.遗传算法在优化问题中的应用研究进展[J].控制与决策.1996,11(4):425-431.
[3]蓝海,王雄,王凌.复杂函数全局最优化的改进遗传退火算法[J].清华大学学报(自然科学版).2002,42(9):1237-1240.
[4]郭立新,武丽梅,李庆忠,等.一种基于多峰值多规则并行搜索的遗传算法[J].机械科学与技术.1999,18(3):406-411.
[5]Yiu-Wing Leung,Yuping Wang.An orthogonal genetic algorithm with quantization for global numerical optimization[J].IEEE transaction on evolutionary computation(S1089-778X).2001,5(1):41-53.
[6]李绍军,王惠,姚平经.求解全局最优化的遗传(GA)-Alopex算法的研究[J].信息与控制.2000,29(4):304-314.
[7]孟红云,刘三阳.基于免疫的多峰极值遗传算法[J].系统工程与电子技术.2003,25(4):477-512.
[8]韩炜,廖振鹏.一种全局优化算法:遗传算法----单纯型法[J].地震工程与工程振动.2001,21(2):6-12.
[9]雷德明.利用混沌搜索全局最优解的一种混合遗传算法[J].系统工程与电子技术.1999,21(12):80-81.
[10]谢巍,方康玲.一种求解不可微非线性函数的全局解的混合遗传算法[J].控制理论与应用.2000,17(2):180-183.
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