Diferenças entre edições de "Programação linear"

978 bytes adicionados ,  11h21min de 19 de setembro de 2005
 
Entretanto, a performance prática do algoritmo de Khachiyan é desapontadora: geralmente, o método simplex é mais eficiente. Sua grande importância é que ele encoraja a pesquisa de [[interior point method]]s. Ao contrário de algoritmo simplex, que apenas evolui ao longo de pontos na fronteira da região factível, métodos de ponto interior podem se mover pelo interior da região factível.
 
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In [[1984]], [[Narendra Karmarkar|N. Karmarkar]] proposed the [[projective method]]. This is the first algorithm performing well both in theory and in practice: Its worst-case complexity is polynomial and experiments on practical problems show that it is reasonably efficient compared to the simplex algorithm. Since then, many interior point methods have been proposed and analysed. A popular interior point method is the [[Mehrotra predictor-corrector method]], which performs very well in practice even though little is known about it theoretically.
 
The current opinion is that the efficiency of good implementations of simplex-based methods and interior point methods is similar for routine applications of linear programming.
 
LP solvers are in widespread use for optimization of various problems in industry, such as optimization of flow in transportation networks, many of which can be transformed into linear programming problems only with some difficulty.
 
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==Variáveis Inteiras ==
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