Post-Optimal Analysis of Linear Semi-Infinite Programs

M.A. Goberna ()
Additional contact information
M.A. Goberna: University of Alicante

A chapter in Optimization and Optimal Control, 2010, pp 23-53 from Springer

Abstract: 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 (search for similar items in EconPapers)
Date: 2010
References: Add references at CitEc
Citations: View citations in EconPapers (1)

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-0-387-89496-6_2

Ordering information: This item can be ordered from
http://www.springer.com/9780387894966

DOI: 10.1007/978-0-387-89496-6_2

Access Statistics for this chapter

More chapters in Springer Optimization and Its Applications from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().