Improving the efficiency of DC global optimization methods by improving the DC representation of the objective function

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Abstract

There are infinitely many ways of representing a d.c. function as a difference of convex functions. In this paper we analyze how the computational efficiency of a d.c.optimization algorithm depends on the representation we choose for the objective function, and we address the problem of characterizing and obtaining a computationally optimal representation. We introduce some theoretical concepts which are necessary for this analysis and report some numerical experiments. © 2008 Springer Science+Business Media, LLC.
Original languageEnglish
Pages (from-to)513-531
JournalJournal of Global Optimization
Volume43
DOIs
Publication statusPublished - 1 Apr 2009

Keywords

  • Branch and bound
  • Dc program
  • Dc representation
  • Outer approximation
  • Semi-infinite program

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