Difference between revisions of "Interior-point method for LP"

From optimization
Jump to: navigation, search
(Introduction)
(Introduction)
Line 3: Line 3:
  
 
=Introduction=
 
=Introduction=
The Interior-Point method relies on having a linear programming model with the objective function and all constraints being continuous and twice continuously differentiable.
+
Interior point methods are a type of algorithms that are used in solving both linear and nonlinear convex optimization problems.convex optimization problems that contain inequalities as constraints.The Interior-Point method relies on having a linear programming model with the objective function and all constraints being continuous and twice continuously differentiable.
  
 
=Uses=
 
=Uses=

Revision as of 15:22, 25 May 2014

Claimed by John Plaxco, Alex Valdes, Wojciech Stojko.
Sources 4 and 5 have a chapter each devoted to our topic. Source 3 has a long section of chapters. Other two sources mention it, and the rest of the books do not have the topic.

Contents

Introduction

Interior point methods are a type of algorithms that are used in solving both linear and nonlinear convex optimization problems.convex optimization problems that contain inequalities as constraints.The Interior-Point method relies on having a linear programming model with the objective function and all constraints being continuous and twice continuously differentiable.

Uses

Algorithm

Example

Conclusion

Sources

1. T.F. Edgar, D.M. Himmelblau, L.S. Lasdon, Optimization of chemical processes (pp 242-291). McGraw-Hill, 2001
2. Bradley, Hax, and Magnanti, Applied Mathematical Programming (p 413).
3. R.J. Vanderbei, Linear Programming: Foundations and Extensions (Chp 17-22). Springer, 2008.
4. J. Nocedal, S. J. Wright, Numerical optimization (Chp 14). Springer, 1999.
5. S. Boyd, L. Vandenberghe, Convex Optimization (Chp 11). Cambridge University Press, 2009