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A framework of quantum-inspired multi-objective evolutionary algorithms and its convergence condition

Published: 07 July 2007 Publication History

Abstract

A general framework of quantum-inspired multi-objective evolutionary algorithms as well as one of its sufficient convergence conditions to Pareto optimal set is proposed.

References

[1]
Rudolph, G., and Agapie, A. Convergence Properties of Some Multi-Objective Evolutionary Algorithms. in the 2000 Congress on Evolutionary Computation (CEC 2000). 2000. Piscataway (NJ): IEEE Press.
[2]
Hanne, T. A multiobjective evolutionary algorithm for approximating the efficient set. European Journal of Operational Research, 2007. 176: p. 1723--1734.
[3]
Kim, Y., Kim, J.-H., and Han, K.-H. Quantum-inspired Multiobjective Evolutionary Algorithm for Multiobjective 0/1 Knapsack Problems. in 2006 IEEE Congress on Evolutionary Computation. 2006. Canada: IEEE Press.
[4]
Li, Z., and Rudolph, G. A Framework of Quantum-inspired Multi-Objective Evolutionary Algorithms and its Convergence Properties. Technical Report CI 228/07, SFB 531, Universitat Dortmund, 2007.

Cited By

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  • (2014)Applications of quantum inspired computational intelligenceArtificial Intelligence Review10.1007/s10462-012-9330-642:1(79-156)Online publication date: 1-Jun-2014
  • (2013)The Research and Summary of Evolutionary Multi-objective Optimization AlgorithmIntelligence Computation and Evolutionary Computation10.1007/978-3-642-31656-2_72(505-512)Online publication date: 2013
  • (2010)Novel multi-objective genetic algorithm based on static bayesian game strategyProceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I10.1007/978-3-642-13495-1_75(612-619)Online publication date: 12-Jun-2010
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  1. A framework of quantum-inspired multi-objective evolutionary algorithms and its convergence condition

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    Published In

    cover image ACM Conferences
    GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation
    July 2007
    2313 pages
    ISBN:9781595936974
    DOI:10.1145/1276958

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 07 July 2007

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    Author Tags

    1. Pareto optimal set
    2. multi-objective evolutionary algorithms
    3. quantum computing
    4. stochastic convergence

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    GECCO '07 Paper Acceptance Rate 266 of 577 submissions, 46%;
    Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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    Cited By

    View all
    • (2014)Applications of quantum inspired computational intelligenceArtificial Intelligence Review10.1007/s10462-012-9330-642:1(79-156)Online publication date: 1-Jun-2014
    • (2013)The Research and Summary of Evolutionary Multi-objective Optimization AlgorithmIntelligence Computation and Evolutionary Computation10.1007/978-3-642-31656-2_72(505-512)Online publication date: 2013
    • (2010)Novel multi-objective genetic algorithm based on static bayesian game strategyProceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I10.1007/978-3-642-13495-1_75(612-619)Online publication date: 12-Jun-2010
    • (2009)Multi-objective particle swarm optimization algorithm based on game strategiesProceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation10.1145/1543834.1543873(287-294)Online publication date: 12-Jun-2009
    • (2009)Convergence performance comparison of quantum-inspired multi-objective evolutionary algorithmsComputers & Mathematics with Applications10.1016/j.camwa.2008.10.04657:11-12(1843-1854)Online publication date: 1-Jun-2009

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