An approximate approach of global optimization for polynomial programming problems

Han-Lin Li*, Ching Ter Chang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Many methods for solving polynomial programming problems can only find locally optimal solutions. This paper proposes a method for finding the approximately globally optimal solutions of polynomial programs. Representing a bounded continuous variable xi as the addition of a discrete variable di and a small variable εi, a polynomial term xixj can be expanded as the sum of dixj, djεi and εiεj. A procedure is then developed to fully linearize dixj and djεi, and to approximately linearize εiεj with an error below a pre-specified tolerance. This linearization procedure can also be extended to higher order polynomial programs. Several polynomial programming examples in the literature are tested to demonstrate that the proposed method can systematically solve these examples to find the global optimum within a pre-specified error.

Original languageEnglish
Pages (from-to)625-632
Number of pages8
JournalEuropean Journal of Operational Research
Volume107
Issue number3
DOIs
StatePublished - 16 Jun 1998

Keywords

  • Global optimization
  • Linearization
  • Polynomial program

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