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. 

“Each chapter can be read by its own and does not assume knowledge from one of the other chapters. … All in all, the book ‘Nonlinear combinatorial optimization’ introduces some interesting topics in this relatively new field.” (Isabel Beckenbach, zbMATH 1480.90209, 2022)