Difference between revisions of "Interior-point method for LP"
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== Sources == | == Sources == | ||
| − | 1 | + | 1. R.J. Vanderbei, Linear Programming: Foundations and Extensions (Chp 17-22). Springer, 2008.<br> |
| − | + | 2. J. Nocedal, S. J. Wright, Numerical optimization (Chp 14). Springer, 1999. <br> | |
| − | + | 3. S. Boyd, L. Vandenberghe, Convex Optimization (Chp 11). Cambridge University Press, 2009 | |
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Revision as of 15:23, 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. R.J. Vanderbei, Linear Programming: Foundations and Extensions (Chp 17-22). Springer, 2008.
2. J. Nocedal, S. J. Wright, Numerical optimization (Chp 14). Springer, 1999.
3. S. Boyd, L. Vandenberghe, Convex Optimization (Chp 11). Cambridge University Press, 2009
