An enhanced logarithmic method for signomial programming with discrete variables

Han-Lin Li, Shu Cherng Fang, Yao Huei Huang*, Tiantian Nie

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Signomial programming problems with discrete variables (SPD) appear widely in real-life applications, but they are hard to solve. This paper proposes an enhanced logarithmic method to reformulate the SPD problem as a mixed 0-1 linear program (MILP) with a minimum number of binary variables and inequality constraints. Both of the theoretical analysis and numerical results strongly support its superior performance to other state-of-the-art linearization methods. We also extend the proposed method to linearize some more complicated problems involving product and fractional terms in discrete and continuous variables.

Original languageEnglish
Pages (from-to)922-934
Number of pages13
JournalEuropean Journal of Operational Research
Volume255
Issue number3
DOIs
StatePublished - 1 Dec 2016

Keywords

  • Linearization technique
  • Mixed 0-1 linear programming
  • Signomial programming

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