Abstract
A striking fact about nonconvex global optimization which was shown in Chapter 1 is that, with all their diversity, virtually every nonconvex optimization problem can be described in terms of d.c. functions (differences of convex functions) and/or d.c. sets (differences of convex sets). This pervasiveness of the d.c. structure makes it a very convenient framework for a unified approach to an extremely broad class of problems at first sight very different from each other. For the design of efficient solution methods for these problems, it is, therefore, necessary to understand the d.c. structure.
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© 1997 Springer Science+Business Media Dordrecht
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Konno, H., Thach, P.T., Tuy, H. (1997). D.C. Functions and D.C. Sets. In: Optimization on Low Rank Nonconvex Structures. Nonconvex Optimization and Its Applications, vol 15. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4098-4_3
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DOI: https://doi.org/10.1007/978-1-4615-4098-4_3
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-6835-9
Online ISBN: 978-1-4615-4098-4
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