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'''Mixed Complementarity Problem''' ('''MCP''') is a problem formulation in [[mathematical programming]]. Many well-known problem types are special cases of, or may be reduced to MCP. It is a generalization of [[Nonlinear complementarity problem]] (NCP).
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==Definition==
 
The mixed complementarity problem is defined by a mapping <math>F(x): \mathbb{R}^n \to \mathbb{R}^n</math>, lower values <math>\ell_i \in \mathbb{R} \cup \{-\infty\}</math> and upper values <math>u_i \in \mathbb{R}\cup\{\infty\}</math>.
 
The '''solution''' of the MCP is a vector <math>x \in \mathbb{R}^n</math> such that for each index <math>i \in \{1, \ldots, n\}</math> one of the following alternatives holds:
* <math>x_i = \ell_i, \; F_i(x) \ge 0</math>;
* <math>\ell_i < x_i < u_i, \; F_i(x) = 0</math>;
* <math>x_i = u_i, \; F_i(x) \le 0</math>.
 
Another definition for MCP is: it is a [[variational inequality]] on the [[parallelepiped]] <math>[\ell, u]</math>.
 
== See also ==
* [[Complementarity theory]]
 
== References ==
 
* {{cite paper|author=Stephen C. Billups|title=Algorithms for complementarity problems and generalized equations|date=1995|
url=ftp://ftp.cs.wisc.edu/math-prog/tech-reports/95-14.ps|
format=[[Adobe Photoshop|PS]]|accessdate=2006-08-14}}
* {{cite book|author=Francisco Facchinei, Jong-Shi Pang|title=Finite-Dimensional Variational Inequalities and Complementarity Problems, Volume I|date=2003}}
 
{{Mathematical programming}}
 
[[Category:Mathematical optimization]]

Latest revision as of 00:29, 5 May 2014

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