Quantum algorithms and the genetic code

Hegen Xiong, Kai Xiong, Qiuhua Tang

Quantum genetic algorithm is a recently proposed new optimization algorithm combining quantum algorithm with genetic algorithm. It characterizes good population diversity, rapid convergence and good global search capability and so attracts serious and wide attentions. This paper proposes a novel quantum genetic algorithm called variable-boundary-coded quantum genetic algorithm (vbQGA) in which qubit chromosomes are collapsed into variable-boundary-coded chromosomes instead of binary-coded chromosomes. In this way we can obtain much shorter chromosome strings. 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) proposed by Han in [6]. The 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.

Elena Fimmel, Sergey Valentinovich Petoukhov

Robert Rosén

Ying Sun, Hegen Xiong

Optimization method is important in engineering design and application. 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 variable-boundary-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.

Duong Bui, Kimmo Halunen, Nhan Nguyen +1 more

Lei Li

Through the study of the quantum computing theory and binary coded quantum-inspired evolutionary algorithm, a new real-coded quantum-inspired evolutionary algorithm mode-double parameters real-coded quantum-inspired evolutionary algorithm mode is proposed.When it is applied to the genetic algorithm,a double parameter real-coded quantum genetic algorithm(DRQEA) is obtained.As a result,the binary to decimal conversion and complicated calculation of quantum gate in the quantum bit coded quantum genetic algorithm(QEA) is avoided. Simulation results show that compared with QEA,DRQEAhas lower time complexity,more global search ability which confirms the effectiveness of double parameters real-coded mode.