方向自学习遗传算法.pdfVIP

第35 卷 第17 期 计 算 机 工 程 2009 年9 月 Vol.35 No.17 Computer Engineering September 2009 ·博士论文· 文章编号：1000—3428(2009)17—0014—05 文献标识码：A 中图分类号：TP301.6 方向自学习遗传算法 1,2 1 1 马玉新 ，解建仓 ，罗军刚 (1. 西安理工大学西北水资源与环境生态教育部重点实验室，西安 710048 ；2. 西安电子科技大学发展规划处，西安 710071) 摘 要：为克服准遗传算法收敛速度慢、早熟收敛等缺点，提出一种方向自学习遗传算法，该算法在局部有哪些信誉好的足球投注网站中引入方向信息，利用函数 的伪梯度来指导有哪些信誉好的足球投注网站方向。算法通过个体之间的竞争、合作与学习来不断更新最优个体，为增加种群的多样性提出一种消亡算子，避免早 熟收敛，提高算法收敛速度。采用4 个二维函数和多个无约束高维函数对算法进行测试，与3 个新提出的算法进行比较，实验数据和理论 分析表明，该算法在解的质量上和计算复杂度上都优于上述3 个算法，充分证明该算法的有效性。 关键词：遗传算法；方向自学习；函数优化；进化计算 Genetic Algorithm of Directional Self-learning 1,2 1 1 MA Yu-xin , XIE Jian-cang , LUO Jun-gang (1. Key Lab of Northwest Water Resources and Environment Ecology of Ministry of Education, Xi’an University Technology, Xi’an 710048; 2. Department of Development Planning, Xidian University, Xi’an 710071) 【Abstract 】In order to overcome the disadvantages of classical genetic algorithm of low convergence speed and avoid prematurity, this paper proposes an improved Genetic Algorithm of Directional Self-Learning(DSLGA). The directional information is introduced in local search process of the self-learning operator. And the search direction is guided by the false derivative of the function fitness. By the competition, cooperation and learning among the individuals, best solution is updated continuously. And a deletion operator is proposed to increase diversity. So the prematurity is avoided. In experiments, DSLGA is tested by four bi-dimension functions and three u