دانلود مقاله ISI انگلیسی شماره 150205
ترجمه فارسی عنوان مقاله

دروازه چرخش کوانتومی در الگوریتم تکاملی الهام گرفته از کوانتوم: یک بررسی، تجزیه و تحلیل و مطالعه مقایسهای

عنوان انگلیسی
Quantum rotation gate in quantum-inspired evolutionary algorithm: A review, analysis and comparison study
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
150205 2018 24 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Swarm and Evolutionary Computation, Available online 27 February 2018

ترجمه کلمات کلیدی
الگوریتم تکاملی الهام گرفته از کوانتومی، دروازه چرخش کوانتومی، مشکل بهینه سازی عملکرد مشکل حلقه
کلمات کلیدی انگلیسی
Quantum-inspired evolutionary algorithm; Quantum rotation gate; Function optimization problem; Knapsack problem;
پیش نمایش مقاله
پیش نمایش مقاله  دروازه چرخش کوانتومی در الگوریتم تکاملی الهام گرفته از کوانتوم: یک بررسی، تجزیه و تحلیل و مطالعه مقایسهای

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.