Abstract
This chapter presents an introduction to the class of mixed-integer nonlinear MINLP optimization problems. Section 20.1 presents the motivation for studying MINLP problems. Section 20.2 discusses the mathematical formulation and outlines the theoretical and algorithmic challenges. Section 20.3 provides an overview of the local MINLP optimization algorithms which can address convex MINLP problems rigorously. Finally, section 20.4 outlines the global MINLP optimization approaches for nonconvex MINLP optimization problems.
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© 2000 Springer Science+Business Media Dordrecht
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Floudas, C.A. (2000). Introduction to Nonlinear and Mixed-Integer Optimization. In: Deterministic Global Optimization. Nonconvex Optimization and Its Applications, vol 37. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4949-6_20
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DOI: https://doi.org/10.1007/978-1-4757-4949-6_20
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4419-4820-5
Online ISBN: 978-1-4757-4949-6
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