A Fast Algorithm for Linearly Constrained Quadratic Programming Problems with Lower and Upper Bounds

2008 ◽  
Author(s):  
Yanwu Liu ◽  
Zhongzhen Zhang
Keyword(s):  
Quadratic Programming ◽  
Fast Algorithm ◽  
Upper Bounds ◽  
Lower And Upper Bounds ◽  
Quadratic Programming Problems ◽  
Linearly Constrained

scholarly journals Optimal control of a chemical reactor

1997 ◽  
Vol 39 (1) ◽  
pp. 61-76
Author(s):  
K. H. Wong ◽  
N. Lock
Keyword(s):  
Optimal Control ◽  
Finite Element ◽  
Differential Equations ◽  
Quadratic Programming ◽  
Original Problem ◽  
Chemical Reactor ◽  
Galerkin Scheme ◽  
Actual Output ◽  
Quadratic Programming Problems ◽  
Linearly Constrained

AbstractA chemical reactor problem is considered governed by partial differential equations. We wish to control the input temperature and the input oxygen concentration so that the actual output temperature can be as close to the desired output temperature as possible. By linearizing the differential equations around a nominal equation and then applying a finite-element Galerkin Scheme to the resulting system, the original problem can be converted into a sequence of linearly-constrained quadratic programming problems.

Extension of the Spatial PDI Model to Three Dimensions

1997 ◽  
Vol 84 (1) ◽  
pp. 176-178
Author(s):  
Frank O'Brien
Keyword(s):  
Population Density ◽  
Dimensional Space ◽  
Finite Lattice ◽  
Three Dimensional ◽  
Upper Bounds ◽  
Three Dimensions ◽  
Lower And Upper Bounds ◽  
Density Index ◽  
Three Dimensional Space

The author's population density index ( PDI) model is extended to three-dimensional distributions. A derived formula is presented that allows for the calculation of the lower and upper bounds of density in three-dimensional space for any finite lattice.

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