一种用于进化算法历史计算数据的高效利用方法
进化算法由于其强大的系统建模能力和空间搜索能力已被广泛应用于许多实际问题的求解中。然而，在算法进化的过程中存在个体适应值重复计算的问题，尤其在解决实际工程中的复杂问题时，适应值的计算会消耗大量时间。为此，利用哈希表的高速存取能力，将哈希表用于存取适应值的历史计算数据，从而避免优化过程中适应值的重复计算，并且对优化结果没有任何影响。仿真实验结果验证了此方法的有效性。...
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| Published in | 计算机工程与科学 Vol. 38; no. 1; pp. 62 - 66 |
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| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
太原科技大学工业与系统工程研究所,山西太原,030024
2016
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| Subjects | |
| Online Access | Get full text |
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| Abstract | 进化算法由于其强大的系统建模能力和空间搜索能力已被广泛应用于许多实际问题的求解中。然而，在算法进化的过程中存在个体适应值重复计算的问题，尤其在解决实际工程中的复杂问题时，适应值的计算会消耗大量时间。为此，利用哈希表的高速存取能力，将哈希表用于存取适应值的历史计算数据，从而避免优化过程中适应值的重复计算，并且对优化结果没有任何影响。仿真实验结果验证了此方法的有效性。 |
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| AbstractList | 进化算法由于其强大的系统建模能力和空间搜索能力已被广泛应用于许多实际问题的求解中。然而，在算法进化的过程中存在个体适应值重复计算的问题，尤其在解决实际工程中的复杂问题时，适应值的计算会消耗大量时间。为此，利用哈希表的高速存取能力，将哈希表用于存取适应值的历史计算数据，从而避免优化过程中适应值的重复计算，并且对优化结果没有任何影响。仿真实验结果验证了此方法的有效性。 TP301; 进化算法由于其强大的系统建模能力和空间搜索能力已被广泛应用于许多实际问题的求解中.然而,在算法进化的过程中存在个体适应值重复计算的问题,尤其在解决实际工程中的复杂问题时,适应值的计算会消耗大量时间.为此,利用哈希表的高速存取能力,将哈希表用于存取适应值的历史计算数据,从而避免优化过程中适应值的重复计算,并且对优化结果没有任何影响.仿真实验结果验证了此方法的有效性. |
| Author | 闫盼 谭瑛 张建华 |
| AuthorAffiliation | 太原科技大学工业与系统工程研究所,山西太原030024 |
| AuthorAffiliation_xml | – name: 太原科技大学工业与系统工程研究所,山西太原,030024 |
| Author_FL | ZHANG Jian-hua TAN Ying YAN Pan |
| Author_FL_xml | – sequence: 1 fullname: YAN Pan – sequence: 2 fullname: TAN Ying – sequence: 3 fullname: ZHANG Jian-hua |
| Author_xml | – sequence: 1 fullname: 闫盼 谭瑛 张建华 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DOI | 10.3969/j.issn.1007-130X.2016.01.010 |
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| DocumentTitleAlternate | A method of using historical calculation data efficiently in evolutionary algorithms |
| DocumentTitle_FL | A method of using historical calculation data efficiently in evolutionary algorithms |
| EndPage | 66 |
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| Keywords | 进化算法 hash table 历史计算数据 historical calculation data 哈希表 evolutionary algorithms |
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| Notes | YAN Pan,TAN Ying,ZHANG Jian-hua （Institute of Industrial and System Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China） hash table; historical calculation data ; evolutionary algorithms 43-1258/TP Evolutionary algorithms have been widely used in practical problems for their remarkable system modeling capability and spatial searching capability. However, there is a problem of repetitive computation for individual fitness in the process of evolutionary algorithms. Especially when solving complex engineering problems, fitness calculations can expend a large amount of time. The hash table features high-speed access capability, which can be used to access historical data of fitness and solve repetitive computation problem of individual fitness during the optimization process without affecting the results. Simulation results prove the efficiency of the proposal. |
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| SubjectTerms | 历史计算数据 哈希表 进化算法 |
| Title | 一种用于进化算法历史计算数据的高效利用方法 |
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