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Convexification and Global Optimization in Continuous and Mixed-Integer Nonlinear Programming

The aim of this book is to marry the advancements in solving nonlinear and integer programming models and to develop new results in the more general framework of mixed-integer nonlinear programs (MINLPs) with the goal of devising practically efficient global optimization algorithms for MINLPs
Type:
Book
Area:
Optimization
Target Group:
Advanced
DOI:
https://doi.org/10.1007/978-1-4757-3532-1
Link:
https://link.springer.com/book/10.1007/978-1-4757-3532-1
Cite as:
Tawarmalani, Mohit & Sahinidis, Nikolaos. (2002). Convexification and global optimization in continuous and mixed-integer nonlinear programming. Theory, algorithms, software, and applications. 10.1007/978-1-4757-3532-1.
Author of the review:
Ivo Nowak
HAW Hamburg


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