Function Optimization Based on Quantum Genetic Algorithm
Quantum genetic algorithm has the characteristics of good
population diversity, rapid convergence and good global search
capability and so on.It combines quantum algorithm with genetic
algorithm. A novel quantum genetic algorithm is proposed ,which
is called variable-boundary-coded quantum genetic algorithm
(vbQGA) in which qubit chromosomes are collapsed into variableboundary-
coded chromosomes instead of binary-coded
chromosomes. Therefore much shorter chromosome strings can be
gained.The method of encoding and decoding of chromosome is
first described before a new adaptive selection scheme for angle
parameters used for rotation gate is put forward based on the core
ideas and principles of quantum computation. Eight typical
functions are selected to optimize to evaluate the effectiveness and
performance of vbQGA against standard genetic algorithm (sGA)
and genetic quantum algorithm (GQA). The simulation results
show that vbQGA is significantly superior to sGA in all aspects
and outperforms GQA in robustness and solving velocity,
especially for multidimensional and complicated functions.
Keywords: function optimization; quantum genetic algorithm; variable-boundary coding; optimization algorithm
Download Full-Text
ABOUT THE AUTHORS
Ying Sun
College of Machinery and Automation, B.O.X 242, Wuhan University of Science and Technology, Wuhan, 430081, China
Yuesheng Gu
2Department of Computer Science, Henan Institute of Science and Technology, Xinxiang 453003, Henan, China
Hegen Xiong
College of Machinery and Automation, B.O.X 242, Wuhan University of Science and Technology, Wuhan, 430081, China
Ying Sun
College of Machinery and Automation, B.O.X 242, Wuhan University of Science and Technology, Wuhan, 430081, China
Yuesheng Gu
2Department of Computer Science, Henan Institute of Science and Technology, Xinxiang 453003, Henan, China
Hegen Xiong
College of Machinery and Automation, B.O.X 242, Wuhan University of Science and Technology, Wuhan, 430081, China