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Nonlinear Combinatorial Optimization 2019 ed. [Mīkstie vāki]

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  • Formāts: Paperback / softback, 315 pages, height x width: 235x155 mm, weight: 498 g, 9 Illustrations, color; 20 Illustrations, black and white; VIII, 315 p. 29 illus., 9 illus. in color., 1 Paperback / softback
  • Sērija : Springer Optimization and Its Applications 147
  • Izdošanas datums: 14-Aug-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 303016196X
  • ISBN-13: 9783030161965
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Nonlinear Combinatorial Optimization 2019 ed.Palielināt
  • Formāts: Paperback / softback, 315 pages, height x width: 235x155 mm, weight: 498 g, 9 Illustrations, color; 20 Illustrations, black and white; VIII, 315 p. 29 illus., 9 illus. in color., 1 Paperback / softback
  • Sērija : Springer Optimization and Its Applications 147
  • Izdošanas datums: 14-Aug-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 303016196X
  • ISBN-13: 9783030161965
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783030161965.html

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. 

Recenzijas

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.