Global Optimization Inspired by Quantum Physics

  • Xiaofei Huang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7928)


Scientists have found that atoms and molecules in nature have an amazing power at finding their global minimal energy states even when their energy landscapes are full of local minima. Recently, the author postulated an optimization algorithm for understanding this fundamental feature of nature. This paper presents a version of this algorithm for attacking continuous optimization problems. On large size benchmark functions, it significantly outperformed the standard particle swarm optimization algorithm.


LDPC Code Hamiltonian Operator Space Location Continuous Optimization Problem Rosenbrock Function 
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  1. 1.
    Huang, X.: Dual schrödinger equation as a global optimization algorithm. In: Advances in Quantum Theory, IEEE Computer Society Press, Vaxjo (2010)Google Scholar
  2. 2.
    Huang, X.: Cooperative optimization for energy minimization in computer vision: A case study of stereo matching. In: Rasmussen, C.E., Bülthoff, H.H., Schölkopf, B., Giese, M.A. (eds.) DAGM 2004. LNCS, vol. 3175, pp. 302–309. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  3. 3.
    Huang, X.: Cooperative optimization for solving large scale combinatorial problems. In: Theory and Algorithms for Cooperative Systems. Series on Computers and Operations Research, pp. 117–156. World Scientific (2004)Google Scholar
  4. 4.
    Huang, X.: Near perfect decoding of LDPC codes. In: Proceedings of IEEE International Symposium on Information Theory (ISIT), pp. 302–306 (2005)Google Scholar
  5. 5.
    Pardalos, P., Resende, M.: Handbook of Applied Optimization. Oxford University Press, Inc (2002)Google Scholar
  6. 6.
    Eberhart, R.C., Kennedy, J.: A new optimizer using particle swarm theory. In: Proceedings of the Sixth International Symposium on Micro Machine and Human Science, pp. 39–43. IEEE Service Center, Nagoya (1995)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Xiaofei Huang
    • 1
  1. 1.eGain CommunicationsMountain ViewU.S.A.

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