6755
2019
eng
237
265
2
11
article
0
2018-09-22
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QPLIB: A Library of Quadratic Programming Instances
This paper describes a new instance library for Quadratic Programming (QP), i.e., the family of continuous and (mixed)-integer optimization problems where the objective function, the constrains, or both are quadratic. QP is a very diverse class of problems, comprising sub-classes of problems ranging from trivial to undecidable. This diversity is reflected in the variety of solution methods for QP, ranging from entirely combinatorial ones to completely continuous ones, including many for which both aspects are fundamental. Selecting a set of instances of QP that is at the same time not overwhelmingly onerous but sufficiently challenging for the many different interested communities is therefore important. We propose a simple taxonomy for QP instances that leads to a systematic problem selection mechanism. We then briefly survey the field of QP, giving an overview of theory, methods and solvers. Finally, we describe how the library was put together, and detail its final contents.
Mathematical Programming Computation
10.1007/s12532-018-0147-4
yes
Fabio Furini
Ambros Gleixner
Emiliano Traversi
Pietro Belotti
Antonio Frangioni
Ambros Gleixner
Nick Gould
Leo Liberti
Andrea Lodi
Ruth Misener
Hans Mittelmann
Nikolaos V. Sahinidis
Stefan Vigerske
Angelika Wiegele
Mathematical Optimization
Mathematical Optimization Methods
Gleixner, Ambros
Vigerske, Stefan
MIP-ZIBOPT
MODAL-SynLab
MODAL-Gesamt