Semi-infinite programming
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In optimization theory, semi-infinite programming (SIP) is an optimization problem with a finite number of variables and an infinite number of constraints, or an infinite number of variables and a finite number of constraints. In the former case the constraints are typically parameterized.cite-ref-1[1]
Contents
• Examples
• See also
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Mathematical formulation of the problem
The problem can be stated simply as:
min x ∈ ∈ X f ( x ) {\displaystyle \min _{x\in X}\;\;f(x)}
subject to: {\displaystyle {\text{subject to: }}}
g ( x , y ) ≤ ≤ 0 , ∀ ∀ y ∈ ∈ Y {\displaystyle g(x,y)\leq 0,\;\;\forall y\in Y}
where
f : R n → → R {\displaystyle f:R^{n}\to R}
g : R n × × R m → → R {\displaystyle g:R^{n}\times R^{m}\to R}
X ⊆ ⊆ R n {\displaystyle X\subseteq R^{n}}
Y ⊆ ⊆ R m . {\displaystyle Y\subseteq R^{m}.}
SIP can be seen as a special case of bilevel programs in which the lower-level variables do not participate in the objective function.
Methods for solving the problem
In the meantime, see external links below for a complete tutorial.
Examples
In the meantime, see external links below for a complete tutorial.
See also
References
cite-note-11. ↑ Bonnans & Shapiro 2000, pp. 496–526, 581 Goberna & López 1998 Hettich & Kortanek 1993, pp. 380–429
• citerefgobernal-pez1998Goberna, M.A.; López, M.A. (1998). Linear Semi-Infinite Optimization. Wiley.
• citerefguerra-v-zquezr-ckmannsteinstill2008Guerra Vázquez, F.; Rückmann, J.-J.; Stein, O.; Still, G. (1 August 2008). "Generalized semi-infinite programming: A tutorial". Journal of Computational and Applied Mathematics. 217 (2): 394–419. Bibcode:2008JCoAM.217..394G. doi:10.1016/j.cam.2007.02.012.
External links
• Description of semi-infinite programming from INFORMS (Institute for Operations Research and Management Science).