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Cross-Hill: A heuristic method for global optimization

  • Tingting Wu
  • , Deren Han*
  • , Yi Xu
  • *Corresponding author for this work
  • Nanjing University of Posts and Telecommunications
  • Nanjing Normal University
  • Southeast University, Nanjing

Research output: Contribution to journalArticlepeer-review

Abstract

The heuristic Cross-Hill method proposed by Qi et al. (2009) [14] was recently extended from finding the Z-eigenvalues of tensors to quantum separation problem by Han and Qi (2013) [5]. In this paper, we show that it can be extended to solve general global optimization problems. The heuristic Cross-Hill method is a combination of a local optimization method and a global optimization method with lower dimension. At each iteration, it first uses the local optimization method to find a local solution. Then, using this point and an arbitrary orthogonal vector, it solves a two-dimensional optimization problem to find a better solution than that the local approach was able to find. Preliminary experimental results are very encouraging.

Original languageEnglish
Pages (from-to)959-967
Number of pages9
JournalApplied Mathematics and Computation
Volume266
DOIs
StatePublished - 29 Jun 2015
Externally publishedYes

Keywords

  • Cross-Hill
  • Global optimization
  • Gradient descent method
  • Local method
  • Polynomial optimization
  • Tensor

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