| 自适应最优保存的模拟退火遗传调度算法研究及其应用 |
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| 引用本文： | 龙小琼,郁松年.自适应最优保存的模拟退火遗传调度算法研究及其应用[J].计算机工程与应用,2004,40(17):64-66,92. |
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| 作者姓名： | 龙小琼 郁松年 |
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| 作者单位： | 上海大学计算机工程与科学学院,上海,200072 |
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| 基金项目： | 上海市科委自然科学基金项目(编号:00JC14052)，上海市教委项目:网格技术-E研究院资助 |
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| 摘 要： | 该文对调度算法做了简单的介绍。在结合已有的模拟退火算法和遗传算法的基础上,改进了现有的遗传调度算法,自适应地保存最优个体,并对其进行模拟退火。与简单最优保存遗传调度算法进行了比较,结果表明新的算法比原有算法搜索能力更强,在跳出局部最优方面也有改进,有效地解决了原有遗传调度算法的早熟现象。
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| 关 键 词： | 自适应 遗传调度算法 最优保存 模拟退火 DAG图 |
| 文章编号： | 1002-8331-(2004)17-0064-03 |
SAMOAGSA Algorithm Research and Its Application |
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| Long Xiaoqiong Yu,Songnian.SAMOAGSA Algorithm Research and Its Application[J].Computer Engineering and Applications,2004,40(17):64-66,92. |
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| Authors: | Long Xiaoqiong Yu Songnian |
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| Abstract: | This thesis introduces the scheduling algorithm briefly.Based on combination of simulated annealing algorithm(SAA)and genetic algorithm,we have improved the existing genetic scheduling1algorithm and propose a new genetic scheduling algorithm maintaining optima adaptively with simulated annealing(SAMOAGSA).This algorithm can maintain some optimal offspring adaptively and make them simulated annealing.To compare with the simple genetic scheduling algorithm(MOSGSA)on the effectiveness,this algorithm has more strong searching ability that can abandon the local optimal solution and find the global one.So the premature of MOSGSA can be solved efficiently. |
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| Keywords: | adaptive properties genetic scheduling algorithm maintaining optimum simulated annealing Directed Acyclic Graph(DAG) |
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