Non-Fiction Books:


A New Paradigm for Primal-Dual Interior-Point Algorithms

Customer rating

Click to share your rating 0 ratings (0.0/5.0 average) Thanks for your vote!

Share this product

Self-Regularity by Jiming Peng
Save $46.00
$163.99 was $209.99
or 4 payments of $41.00 with Learn more
In stock with supplier

The item is brand new and in-stock in with one of our preferred suppliers. The item will ship from the Mighty Ape warehouse within the timeframe shown below.

Usually ships within 2-3 weeks


Delivering to:

Estimated arrival:

  • Around 28 Jan to 1 Feb using Express Delivery
    Mighty Ape can deliver this product within 1-2 business days (usually overnight) to urban centres across Australia, and some remote areas. Learn more
    Unlikely to arrive before Christmas
  • Around 29 Jan to 5 Feb using standard courier delivery
    Unlikely to arrive before Christmas


Research on interior-point methods (IPMs) has dominated the field of mathematical programming since the 1980s. Two contrasting approaches in the analysis and implementation of IPMs are the so-called small-update and large-update methods, although, until now, there has been a notorious gap between the theory and practical performance of these two strategies. This book comes close to bridging that gap, presenting a new framework for the theory of primal-dual IPMs based on the notion of the self-regularity of a function. The authors deal with linear optimization, nonlinear complementarity problems, semidefinite optimization and second-order conic optimization problems. The framework also covers large classes of linear complementarity problems and convex optimization. The algorithm considered can be interpreted as a path-following method or a potential reduction method. Starting from a primal-dual strictly feasible point, the algorithm chooses a search direction defined by some Newton-type system derived from the self-regular proximity. The iterate is then updated, with the iterates staying in a certain neighbourhood of the central path until an approximate solution to the problem is f

Author Biography

Jiming Peng is Professor of Mathematics at McMaster University and has published widely on nonlinear programming and interior-points methods. Cornelis Roos holds joint professorships at Delft University of Technology and Leiden University. He is an editor of several journals, coauthor of more than 100 papers, and coauthor (with Tamas Terlaky and Jean-Philippe Vial) of "Theory and Algorithms for Linear Optimization". Tamas Terlaky is Professor in the Department of Computing and Software at McMaster University, founding Editor in Chief of "Optimization and Engineering", coauthor of more than 100 papers, and an editor of several journals and two books.
Release date Australia
October 7th, 2002
Country of Publication
United States
Princeton University Press
Product ID

Customer reviews

Nobody has reviewed this product yet. You could be the first!

Write a Review

Marketplace listings

There are no Marketplace listings available for this product currently.
Already own it? Create a free listing and pay just 9% commission when it sells!

Sell Yours Here

Help & options

  • If you think we've made a mistake or omitted details, please send us your feedback. Send Feedback
  • If you have a question or problem with this product, visit our Help section. Get Help
  • Seen a lower price for this product elsewhere? We'll do our best to beat it. Request a better price
Filed under...