Více o knize
Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design provides a roadmap for readers to determine the difficulty of an algorithmic problem by finding an optimal solution or proving complexity results. It gives a practical treatment of algorithmic complexity and guides readers in solving algorithmic problems. The book offers a comprehensive set of problems with solutions as well as in-depth case studies that demonstrate how to assess the complexity of a new problem. Inhaltsverzeichnis Polynomial-Time Algorithms: Exercises: Introduction to Complexity. Divide-and-Conquer. Greedy Algorithms. Dynamic Programming. Amortized Analysis. NP-Completeness and Beyond: NP-Completeness. Exercises on NP-Completeness. Beyond NP-Completeness. Exercises Going beyond NP-Completeness. Reasoning on Problem Complexity: Reasoning to Assess a Problem Complexity. Chains-on-Chains Partitioning. Replica Placement in Tree Networks. Packet Routing. Matrix Product, or Tiling the Unit Square. Online Scheduling. Bibliography. Index.
Nákup knihy
A Guide to Algorithm Design, Anne Benoit, Yves Robert, Frédéric Vivien
- Jazyk
- Rok vydání
- 2013
- product-detail.submit-box.info.binding
- (pevná)
Doručení
Platební metody
Navrhnout úpravu
- Titul
- A Guide to Algorithm Design
- Podtitul
- Paradigms, Methods, and Complexity Analysis
- Jazyk
- anglicky
- Autoři
- Anne Benoit, Yves Robert, Frédéric Vivien
- Vydavatel
- Taylor & Francis Ltd (Sales)
- Rok vydání
- 2013
- Vazba
- pevná
- Počet stran
- 380
- ISBN13
- 9781439825648
- Kategorie
- Počítače, IT, programování
- Anotace
- Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design provides a roadmap for readers to determine the difficulty of an algorithmic problem by finding an optimal solution or proving complexity results. It gives a practical treatment of algorithmic complexity and guides readers in solving algorithmic problems. The book offers a comprehensive set of problems with solutions as well as in-depth case studies that demonstrate how to assess the complexity of a new problem. Inhaltsverzeichnis Polynomial-Time Algorithms: Exercises: Introduction to Complexity. Divide-and-Conquer. Greedy Algorithms. Dynamic Programming. Amortized Analysis. NP-Completeness and Beyond: NP-Completeness. Exercises on NP-Completeness. Beyond NP-Completeness. Exercises Going beyond NP-Completeness. Reasoning on Problem Complexity: Reasoning to Assess a Problem Complexity. Chains-on-Chains Partitioning. Replica Placement in Tree Networks. Packet Routing. Matrix Product, or Tiling the Unit Square. Online Scheduling. Bibliography. Index.