کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8953860 | 1645963 | 2018 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Quantum rotation gate in quantum-inspired evolutionary algorithm: A review, analysis and comparison study
ترجمه فارسی عنوان
دروازه چرخش کوانتومی در الگوریتم تکاملی الهام گرفته از کوانتوم: یک بررسی، تجزیه و تحلیل و مطالعه مقایسهای
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کلمات کلیدی
الگوریتم تکاملی الهام گرفته از کوانتومی، دروازه چرخش کوانتومی، مشکل بهینه سازی عملکرد مشکل حلقه
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
چکیده انگلیسی
Quantum-inspired Evolutionary Algorithm (QEA) is a kind of intelligent algorithm which widely and effectively used in many fields. In QEA, the basic and common operations usually include quantum chromosome observation and quantum gate update. Quantum rotation gate (QRG) is the most commonly used operator for the operation of quantum gate update, which has a significant influence on the performance of QEA. Many kinds of QRGs have been proposed with different methods to set the only parameter of QRG, i.e., rotation angle. In this paper, a study on classification of QRG is first conducted with respect to rotation direction and magnitude of rotation angle by analyzing and summarizing various kinds of QRGs in literature, and then the corresponding definitions, descriptions and analyses are presented. Furthermore, in order to investigate and compare performances of different QRGs, we set 21 kinds of QRG schemes based on the classification of rotation direction and magnitude of rotation angle. Four typical complex function optimization problems and a 0-1 knapsack problem are selected as experiment objects to test the 21 kinds of schemes. Comprehensive processing and analyzing for the experiment data are conducted, which draws some valuable conclusions for the more reasonable and more effective applications of QEA.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Swarm and Evolutionary Computation - Volume 42, October 2018, Pages 43-57
Journal: Swarm and Evolutionary Computation - Volume 42, October 2018, Pages 43-57
نویسندگان
Hegen Xiong, Zhiyuan Wu, Huali Fan, Gongfa Li, Guozhang Jiang,