“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)

• A role of minimum spanning tree.- Discrete Newton method.- An overview of submodular optimization: single- and multi-objectives.- Discrete convex optimization and applications in supply chain management.- Thresholding methods for streaming submodular maximization with a cardinality constraint and its variants.- Nonsubmodular optimization.- On block-structured integer programming and its applications.- Online combinatorial optimization problems with nonlinear objectives.- Solving combinatorial problems with machine learning methods.- Modeling malware propagation dynamics and developing prevention method in wireless sensor networks.- Composed influence in social networks.- Friending.- Optimization on content spread in social network studies.- Interation-aware influence maximization in social networks.- Multi-document extractive summarization as a nonlinear combinatorial optimization- Viral marketing for complementary products.