Linear programming with interval data: A two-level programming approach

Chiang Kao, Shiang Tai Liu

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Linear programming has been widely applied to solving real world problems. The conventional linear programming model requires the parameters to be known constants. In the real world, however, the parameters are seldom known exactly and have to be estimated. This chapter discusses the general interval linear programming problems where all the parameters, including the cost coefficients, requirement coefficients, and technological coefficients, are represented by interval data. Since the parameters are interval-valued, the objective value is interval-valued as well. A pair of two-level mathematical programs is formulated to calculate the lower bound and upper bound of the objective values of the interval linear program. The two-level mathematical programs are then transformed into one-level nonlinear programs. Solving the pair of nonlinear programs produces the interval of the objective values of the problem. An example illustrates the whole idea and sheds some light on interval linear programming.

Original languageEnglish
Title of host publicationSpringer Optimization and Its Applications
PublisherSpringer International Publishing
Pages63-77
Number of pages15
DOIs
Publication statusPublished - 2013 Jan 1

Publication series

NameSpringer Optimization and Its Applications
Volume76
ISSN (Print)1931-6828
ISSN (Electronic)1931-6836

All Science Journal Classification (ASJC) codes

  • Control and Optimization

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