On the properties of ε-sensitivity analysis for linear programming

Chan Kyoo Park, Woo J.E. Kim, Soondal Park

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

ε-Sensitivity analysis (ε-SA) is a kind of method to perform sensitivity analysis for linear programming. Its main advantage is that it can be directly applied for interior-point methods with a little computation. In this paper, we discuss the property of ε-SA analysis and its relationship with other sensitivity analysis methods. First, we present a new property of ε-SA, from which we derive a simplified formula for finding the characteristic region of ε-SA. Next, based on the simplified formula, we show that the characteristic region of ε-SA includes the characteristic region of Yildirim and Todd's method. Finally, we show that the characteristic region of ε-SA asymptotically becomes a subset of the characteristic region of sensitivity analysis using optimal partition. Our results imply that ε-SA can be used as a practical heuristic method for approximating the characteristic region of sensitivity analysis using optimal partition.

Original languageEnglish
Pages (from-to)135-151
Number of pages17
JournalAsia-Pacific Journal of Operational Research
Volume22
Issue number2
DOIs
StatePublished - Jun 2005

Keywords

  • Interior-point method
  • Linear programming
  • Optimal partition
  • Sensitivity analysis

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