Title :
Improved Quantum Evolutionary Algorithm for Combinatorial Optimization Problem
Author :
Zhang, Rui ; Gao, Hui
Author_Institution :
Harbin Univ. of Sci. & Technol., Harbin
Abstract :
The method of calculating rotation angle of quantum rotation gate plays an important role to the performance of quantum evolutionary algorithm (QEA). This paper proposes an improved quantum evolutionary algorithm (IQEA), whose core is that a new approach of adaptive calculating rotation angle of quantum rotation gate is designed on the basis of the probability amplitude ratio of the corresponding states. Rapid convergence and good global search capability characterize the performance of IQEA. Based on a typical combinatorial optimization problem - 0/1 knapsack problems, the influence of the relative parameter to the performance of IQEA is demonstrated, and then comparing experiments have been done. The results show that IQEA is superior to the previous quantum evolutionary algorithm.
Keywords :
combinatorial mathematics; evolutionary computation; optimisation; quantum computing; combinatorial optimization problem; global search capability; improved quantum evolutionary algorithm; knapsack problem; probability amplitude ratio; quantum rotation gate; Algorithm design and analysis; Automation; Biological cells; Convergence; Cybernetics; Evolutionary computation; Machine learning; Optimization methods; Probability; Quantum computing; Combinatorial optimization; Improved quantum evolutionary algorithm; Knapsack problem; Quantum evolutionary algorithm; Quantum rotation gate;
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
DOI :
10.1109/ICMLC.2007.4370753