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Nonlinear Combinatorial Optimization

Ding-Zhu Du (Hrsg.), Panos M. Pardalos (Hrsg.), Zhao Zhang (Hrsg.)

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Springer International Publishing img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Sonstiges

Beschreibung

Graduate students and researchers in applied mathematics, optimization, engineering,  computer science, and  management science will find this book a useful reference which provides an introduction to applications and fundamental theories in nonlinear combinatorial optimization. Nonlinear combinatorial optimization is a new research area within combinatorial optimization and includes numerous applications to technological developments, such as wireless communication, cloud computing, data science, and social networks. Theoretical developments including discrete Newton methods, primal-dual methods with convex relaxation, submodular optimization, discrete DC program, along with several applications are discussed and explored in this book through articles by leading experts. 

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Schlagwörter

convex relaxation, primal-dual methods with convex relaxation, Fractional Integer Progmanmming, optimization in machine learning, nonlinear assignment problems, discrete Newton methods, nonlinear function, scheduling with energy allocation, heterogeneous sensor systems, optimization in data network designs, combinatorics, discrete convex analysis, combinatorial optimization, submodular optimization, spanning tree in wireless networks, homogeneous sensor systems