Uncertainty analysis on the righthand side for MILP problems

Zhenya Jia, Marianthi Ierapetritou

Research output: Contribution to journalArticlepeer-review

19 Scopus citations

Abstract

A systematic framework is developed to solve the parametric mixed integer linear programming (pMILP) problems where uncertain parameters are present on the righthand side (RHS) of the constraints. For the case of multiple uncertain parameters, a new algorithm of multiparametric linear programming (mpLP) is proposed, which solves a number of nonlinear problems (NLP) iteratively. At each iteration, a point at which the objective value cannot be represented by the current optimal functions is found, and the new optimal function is included in the next iteration. Given the range of uncertain parameters in a MILP problem, the output of this proposed framework is a set of optimal integer solutions and their corresponding critical regions and optimal functions. A number of examples are presented to illustrate the applicabilities of the proposed approach and comparison with existing techniques.

Original languageEnglish (US)
Pages (from-to)2486-2495
Number of pages10
JournalAIChE Journal
Volume52
Issue number7
DOIs
StatePublished - Jul 1 2006

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Environmental Engineering
  • Chemical Engineering(all)

Keywords

  • Mixed integer linear programming
  • Parametric
  • Uncertainty

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