xinghuanlai Associate Professor

Supervisor of Doctorate Candidates

Supervisor of Master's Candidates

  

  • Education Level: PhD graduate

  • Professional Title: Associate Professor

  • Alma Mater: 英国诺丁汉大学

  • Supervisor of Doctorate Candidates

  • Supervisor of Master's Candidates

  • School/Department: 计算机与人工智能学院

  • Discipline:Communications and Information Systems
    Computer Science and Technology
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    Recommended Ph.D.Supervisor Recommended MA Supervisor
    Language: 中文

    Paper Publications

    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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