Abstract
In this chapter nonconvex quadratic programming test problems are considered. These test problems have a quadratic objective function and linear constraints. Quadratic programming has numerous applications (Pardalos and Rosen (1987), Floudas and Visweswaran (1995)) and plays an important role in many nonlinear programming methods. Recent methods of generating challenging quadratic programming test problems and disjointly constrained bilinear programming test problems can be found in the work of Vicente et al. (1992) and Calamai et al. (1993). Furthermore, a very broad class of difficult combinatorial optimization problems such as integer programming, quadratic assignment, and the maximum clique problem can be formulated as nonconvex quadratic programming problems.
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© 1999 Springer Science+Business Media Dordrecht
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Floudas, C.A. et al. (1999). Quadratic Programming Problems. In: Handbook of Test Problems in Local and Global Optimization. Nonconvex Optimization and Its Applications, vol 33. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3040-1_2
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DOI: https://doi.org/10.1007/978-1-4757-3040-1_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4812-0
Online ISBN: 978-1-4757-3040-1
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