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Nonlinear combinatorial optimization

Du, Ding-Zhu.

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Nonlinear combinatorial optimization

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Nonlinear combinatorial optimization/ edited by Ding-Zhu Du, Panos M. Pardalos, Zhao Zhang.
其他作者:	Du, Ding-Zhu.
出版者:	Cham :Springer International Publishing : : 2019.,
面頁冊數:	viii, 315 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer eBooks
標題:	Combinatorial optimization. -
電子資源:	https://doi.org/10.1007/978-3-030-16194-1
ISBN:	9783030161941

Nonlinear combinatorial optimization
Nonlinear combinatorial optimization[electronic resource] /edited by Ding-Zhu Du, Panos M. Pardalos, Zhao Zhang. - Cham :Springer International Publishing :2019. - viii, 315 p. :ill., digital ;24 cm. - Springer optimization and its applications,v.1471931-6828 ;. - Springer optimization and its applications ;v.147..

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.

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.

ISBN: 9783030161941

Standard No.: 10.1007/978-3-030-16194-1doiSubjects--Topical Terms:

544215
Combinatorial optimization.

LC Class. No.: QA402.5 / .N665 2019

Dewey Class. No.: 515.64

Nonlinear combinatorial optimization
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505 0 $a 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.
520 $a 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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