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Nonlinear Combinatorial Optimization
Nonlinear Combinatorial Optimization
Nonlinear Combinatorial Optimization
Nonlinear Combinatorial Optimization

Nonlinear Combinatorial Optimization

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Nonlinear Combinatorial OptimizationAuthor(s): Ding-Zhu Du, Panos M. Pardalos, Zhao Zhang\nFormat: Hardback\nPublisher: Springer Nature Switzerland AG, Switzerland\nImprint: Springer Nature Switzerland AG\nISBN-13: 9783030161934, 978-3030161934\nSynopsis\nGraduate 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 boo.

Nonlinear Combinatorial Optimization

Nonlinear Combinatorial OptimizationAuthor(s): Ding-Zhu Du, Panos M. Pardalos, Zhao Zhang\nFormat: Hardback\nPublisher: Springer Nature Switzerland AG, Switzerland\nImprint: Springer Nature Switzerland AG\nISBN-13: 9783030161934, 978-3030161934\nSynopsis\nGraduate 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 boo.

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