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A Novel Improved Quantum Genetic Algorithm for Combinatorial Optimization Problems
Impact Factor:1.35
Affiliation of Author(s):School of Information Science and Technology, Southwest Jiaotong University, Chengdu, Siehuan 610031
Journal:Acta Electronica Sinica
Funded by:国家自然科学基金(No.10174057,No.90201011);教育部科学技术研究重点项目(No.105148)
Key Words:quantum computation,quantum genetic algorithm,combinatorial optimization
Abstract:Based on quantum genetic algorithm(QGA),a novel improved quantum genetic algorithm(NIQGA)to solve combinatorial optimization problem is proposed.To make full use of interference and entanglement characteristics of quantum state,dynamic step length in adjustment of angle of quantum gate,quantum crossover operation and quantum mutation operation are introduced,therefore high efficiency for optimization is achieved.Two typical combinatorial optimization problems0/1 knapsack problem and route selection problem,are adopted to confirm the performance of NIQGA.Experimental results show that compared with GA and QGA,NIQGA is characterized by fast convergence rate and excellent capability on global optimization,especially better performance for combinatorial optimization problem with less correlation of genes.
Co-author:Huanlai Xing,Wei Pan*,Xihua Zhou
Volume:35
Issue:10
Page Number:1999-2002
Translation or Not:yes
Date of Publication:2007-01-01
Included Journals:EI
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