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Post-Optimal Analysis of Linear Semi-Infinite Programs

  • M.A. GobernaEmail author
Chapter
Part of the Springer Optimization and Its Applications book series (SOIA, volume 39)

Summary

Linear semi-infinite programming (LSIP) deals with linear optimization problems in which either the dimension of the decision space or the number of constraints (but not both) is infinite. In most applications of LSIP to statistics, electronics, telecommunications, and other fields, all the data (or at least part of them) are uncertain. Post-optimal analysis provides answer to questions about the quantitative impact on the optimal value of small perturbations of the data (sensitivity analysis) and also about the continuity properties of the optimal value, the optimal set, and the feasible set (stability analysis) around the nominal problem. This chapter surveys the state of the art in sensitivity and stability analysis in LSIP.

Keywords

linear semi-infinite programming linear inequality systems stability analysis sensitivity analysis 

Notes

Acknowledgment

The author wishes to thank M.J. Cánovas, M.D. Fajardo, and J. Parra for their valuable comments and suggestions.

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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.Department of Statistics and Operations ResearchUniversity of AlicanteAlicanteSpain

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