Title
Quantum rotation gate in quantum-inspired evolutionary algorithm: A review, analysis and comparison study.
Abstract
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.
Year
DOI
Venue
2018
10.1016/j.swevo.2018.02.020
Swarm and Evolutionary Computation
Keywords
Field
DocType
Quantum-inspired evolutionary algorithm,Quantum rotation gate,Function optimization problem,Knapsack problem
Quantum,Magnitude (mathematics),Quantum gate,Evolutionary algorithm,Computer science,Algorithm,Review analysis,Function optimization,Operator (computer programming),Knapsack problem
Journal
Volume
ISSN
Citations 
42
2210-6502
1
PageRank 
References 
Authors
0.40
17
5
Name
Order
Citations
PageRank
Hegen Xiong1162.28
Zhiyuan Wu231.11
Huali Fan310.40
Gongfa Li423943.45
Guozhang Jiang517227.25