Primal-Dual Interior-Point Methods
by Stephen J. Wright
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Description
In the past decade, primal-dual algorithms have emerged as the most important and useful algorithms from the interior-point class. This book presents the major primal-dual algorithms for linear programming in straightforward terms. A thorough description of the theoretical properties of these methods is given, as are a discussion of practical and computational aspects and a summary of current software. This is an excellent, timely, and well-written work. The major primal-dual algorithms show more covered in this book are path-following algorithms (short- and long-step, predictor-corrector), potential-reduction algorithms, and infeasible-interior-point algorithms. A unified treatment of superlinear convergence, finite termination, and detection of infeasible problems is presented. Issues relevant to practical implementation are also discussed, including sparse linear algebra and a complete specification of Mehrotra's predictor-corrector algorithm. Also treated are extensions of primal-dual algorithms to more general problems such as monotone complementarity, semidefinite programming, and general convex programming problems. show lessTags
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- Genres
- Nonfiction, Science & Nature
- DDC/MDS
- 519.72 — Natural sciences & mathematics Mathematics Probabilities and applied mathematics Linear And Nonlinear Programming Linnear Programming
- LCC
- T57.74 .W75 — Technology Technology (General) Industrial engineering. Management Applied mathematics. Quantitative methods Operations research. Systems analysis
- BISAC
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- Languages
- English
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- Paper, Ebook
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- 2
