| 利用改进的遗传算法求解非线性方程组 |
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| 引用本文： | 陈磊[],、霍永亮[].利用改进的遗传算法求解非线性方程组[J].西南师范大学学报(自然科学版),2015,40(1). |
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| 作者姓名： | 陈磊[] 、霍永亮[] |
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| 作者单位： | 1. 重庆师范大学数学学院，重庆401331; 重庆市群与图的理论及其应用重点实验室，重庆永川402160
2. 重庆文理学院数学与财经学院,重庆永川,402160 |
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| 基金项目： | 重庆高校创新团队建设计划项目(KJTD301321)；重庆市群与图的理论及其应用重点实验室开放课题项目(KFJJ1402)． |
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| 摘 要： | 提出一种改进的求解非线性方程组的浮点遗传算法,算法通过把非线性方程组的求解问题转化为约束优化问题,然后将局部搜索信息引入遗传算法,通过改进的变异算子不断调整搜索区域,最终搜索到含有最优解的区域,再利用局部搜索信息提高解的精度.数值实验结果表明,改进后的浮点遗传算法具有较好的全局优化能力和局部搜索能力,且提高了求解的速度和解的精度.
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| 关 键 词： | 遗传算法 非线性方程组 约束优化问题 局部搜索 |
On Solution toNonlinear Equation Group by Means of Improved Genetic Algorithm |
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| CHEN Lei,HUO Yong-liang.On Solution toNonlinear Equation Group by Means of Improved Genetic Algorithm[J].Journal of Southwest China Normal University(Natural Science),2015,40(1). |
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| Authors: | CHEN Lei[] HUO Yong-liang[] |
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| Abstract: | An improved floating genetic algorithmhas been proposed to solvenonlinear equation group ,and-local search information been introduced into the genetic algorithm .The search regionhas continuously beenadjusted by improved operator .And the region containing the optimal solution has beenfound finally . The solution precision can be improved with local search information .The numerical experiment results show that the improved floating genetic algorithm has good local search ability and global optimization ca-pability ,and can improve the speed and accuracy of the solution . |
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| Keywords: | genetic algorithm nonlinear equation group constrained optimization problems local search |
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