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67
The final NETLIBLP results
 Op. Res. Letters
"... The Netlib has now served for 18 years as a repository of LP problem instances available to test new codes and compare performance. But with standard linear programming solvers there is always some uncertainty about the precise values of the optimal solutions. We have implemented a program called pe ..."
Abstract

Cited by 13 (1 self)
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The Netlib has now served for 18 years as a repository of LP problem instances available to test new codes and compare performance. But with standard linear programming solvers there is always some uncertainty about the precise values of the optimal solutions. We have implemented a program called
Robust solutions of Linear Programming problems contaminated with uncertain data
 Mathematical Programming
, 2000
"... Optimal solutions of Linear Programming problems may become severely infeasible if the nominal data is slightly perturbed. We demonstrate this phenomenon by studying 90 LPs from the wellknown NETLIB collection. We then apply the Robust Optimization methodology (BenTal and Nemirovski [13]; El Ghao ..."
Abstract

Cited by 175 (6 self)
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Optimal solutions of Linear Programming problems may become severely infeasible if the nominal data is slightly perturbed. We demonstrate this phenomenon by studying 90 LPs from the wellknown NETLIB collection. We then apply the Robust Optimization methodology (BenTal and Nemirovski [13]; El
Regularization tools – a matlab package for analysis and solution of discrete illposed problems
 Numerical Algorithms
, 1994
"... The software described in this report was originally published in Numerical Algorithms 6 (1994), pp. 1–35. The current version is published in Numer. Algo. 46 (2007), pp. 189–194, and it is available from www.netlib.org/numeralgo and www.mathworks.com/matlabcentral/fileexchangeContents ..."
Abstract

Cited by 287 (8 self)
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The software described in this report was originally published in Numerical Algorithms 6 (1994), pp. 1–35. The current version is published in Numer. Algo. 46 (2007), pp. 189–194, and it is available from www.netlib.org/numeralgo and www.mathworks.com/matlabcentral/fileexchangeContents
Computational Experience with Rigorous Error Bounds for the Netlib Linear Programming Library
 Reliable Computing
, 2006
"... Abstract. The Netlib library of linear programming problems is a well known suite containing many real world applications. Recently it was shown by Ordóñez and Freund that 71 % of these problems are illconditioned. Hence, numerical difficulties may occur. Here, we present rigorous results for this ..."
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Cited by 6 (4 self)
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Abstract. The Netlib library of linear programming problems is a well known suite containing many real world applications. Recently it was shown by Ordóñez and Freund that 71 % of these problems are illconditioned. Hence, numerical difficulties may occur. Here, we present rigorous results
Active Netlib: An Active Mathematical Software Collection for Inquirybased Computational Science and Engineering Education
"... The efficient application of scientific computing techniques requires specialized knowledge of numerical methods and their implementation in mathematical software libraries that many students, scientists, and engineers, working beyond the already strenuous demands of their particular field, must str ..."
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struggle to achieve. Active Netlib addresses this problem by creating an active collection of executable mathematical software deployed on computational servers and accessible over the network from familiar desktop client interfaces. The Netlib mathematical software collection is being extended in a number
order methods and their performance
, 1990
"... last revision July A class of primaldual interior point methods is developed These methods use a higher order Taylor polynomial to approximate a primaldual trajectory dened from an infeasible point A detailed implementation of these methods is given and their computational performance is studied ..."
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Cited by 12 (0 self)
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is studied We give computational results for two di
erent approaches for dening trajectory and using up to th order polynomial In all cases all the tested netlib problems were solved using default settings The use of higher order polynomial on the average results in approximately to reduction
Robust Optimization  Methodology and Applications
"... Robust Optimization (RO) is a modeling methodology, combined with computational tools, to process optimization problems in which the data are uncertain and is only known to belong to some uncertainty set. The paper surveys the main results of RO as applied to uncertain linear, conic quadratic and se ..."
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Cited by 134 (6 self)
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Robust Optimization (RO) is a modeling methodology, combined with computational tools, to process optimization problems in which the data are uncertain and is only known to belong to some uncertainty set. The paper surveys the main results of RO as applied to uncertain linear, conic quadratic
An Overview of HighPerformance Computing and Challenges for the Future. http://www.netlib.org/utk/ people/JackDongarra/talks.htm
, 2006
"... In this talk we examine how high performance computing has changed over the last 10year and look toward the future in terms of trends. These changes have had and will continue to have a major impact on our software. A new generation of software libraries and algorithms are needed for the effective ..."
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Cited by 3 (0 self)
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of computation, depth of memory hierarchies, range of latencies, and increased run–time environment variability will make these problems much harder. We will focus on the redesign of software to fit multicore architectures.
Implementation and computational results for the hierarchical algorithm for making sparse matrices sparser
 CODEN ACMSCU. ISSN 00983500 (print), 15577295 (electronic). URL http://www.acm.org/pubs/citations/journals/ toms/1993193/p419chang/. Cody:1993:AFS
, 1993
"... If A is the (sparse) coefficient matrix of linearequality constraints, for what nonsingular 7 ’ is ~ = TA as sparse as possible, and how can it be efficiently computed? An efficient algorithm for this Sparsity Problem (SP) would be a valuable preprocessor for linearly constrained optimization pro ..."
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Cited by 3 (2 self)
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problems. In a companion paper we developed a twopass approach to solve SP called the Hierarchical Algorithm. In this paper we report on how we implemented the Hierarchical Algorithm into a code called HASP, and our computational experience in testing HASP on the NETLIB linearprogramming problems. We
A New Infeasible InteriorPoint Algorithm for Linear Programming *
"... ABSTRACT In this paper we present an infeasible pathfollowing interiorpoint algorithm for solving linear programs using a relaxed notion of the central path, called quasicentral path, as a central region. The algorithm starts from an infeasible point which satisfies that the norm of the dual condi ..."
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condition is less than the norm of the primal condition. We use weighted sets as proximity measures of the quasicentral path, and a new merit function for making progress toward this central region. We test the algorithm on a set of NETLIB problems obtaining promising numerical results.
Results 1  10
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