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Journal of Global Optimization

, Volume 28, Issue 2, pp 229–238 | Cite as

A Hybrid Descent Method for Global Optimization

  • K.F.C. Yiu
  • Y. Liu
  • K.L. Teo
Article

Abstract

In this paper, a hybrid descent method, consisting of a simulated annealing algorithm and a gradient-based method, is proposed. The simulated annealing algorithm is used to locate descent points for previously converged local minima. The combined method has the descent property and the convergence is monotonic. To demonstrate the effectiveness of the proposed hybrid descent method, several multi-dimensional non-convex optimization problems are solved. Numerical examples show that global minimum can be sought via this hybrid descent method.

Descent method Global minimum Simulating annealing 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • K.F.C. Yiu
    • 2
  • Y. Liu
    • 1
  • K.L. Teo
    • 1
  1. 1.Department of Applied MathematicsHong Kong Polytechnic UniversityKowloonHong Kong
  2. 2.Department of Industrial and Manufacturing Systems EngineeringThe University of Hong KongPokfulamHong Kong

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