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Global Optimization Inspired by Quantum Physics

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

Abstract

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.

Keywords

LDPC Code Hamiltonian Operator Space Location Continuous Optimization Problem Rosenbrock Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

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

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