A Guide to Algorithm Design Paradigms, Methods, and Complexity Analysis Chapman & Hall/CRC Applied Algorithms and Data Structures Series
Auteurs : Benoit Anne, Robert Yves, Vivien Frédéric
Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design: Paradigms, Methods, and Complexity Analysis 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.
Divided into three parts, 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.
- Part I helps readers understand the main design principles and design efficient algorithms.
- Part II covers polynomial reductions from NP-complete problems and approaches that go beyond NP-completeness.
- Part III supplies readers with tools and techniques to evaluate problem complexity, including how to determine which instances are polynomial and which are NP-hard.
Drawing on the authors? classroom-tested material, this text takes readers step by step through the concepts and methods for analyzing algorithmic complexity. Through many problems and detailed examples, readers can investigate polynomial-time algorithms and NP-completeness and beyond.
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.
Yves Robert, École Normale Supérieure de Lyon, Institut Universitaire de France, and Université de Lyon, France
Anne Benoit and Frederic Vivien, École Normale Supérieure de Lyon, France
Date de parution : 08-2013
Ouvrage de 300 p.
15.6x23.4 cm
Disponible chez l'éditeur (délai d'approvisionnement : 15 jours).
Prix indicatif 103,03 €
Ajouter au panierThèmes d’A Guide to Algorithm Design :
Mots-clés :
Hamiltonian Cycle; algorithm design; Vertex Cover; beyond NP-completeness; Competitive Ratio; polynomial reductions; Execution Time; optimal algorithms; Independent Set; algorithmic complexity; Greedy Algorithm; NP-complete problems; Np Complete Problem; solving algorithmic problems; Processor P2; polynomial-time algorithms; Maximum Independent Set; Instance I1; Server J1; Dynamic Programming Algorithm; Integer Linear Program; Processor Pi; Polynomial Time; Polynomial Time Algorithm; Greedy Choice; Binary Search; Task Ti; Np Completeness Proof; Optimal Makespan; Bipartite Graph; Clause C1; Task Tj; Floyd Warshall Algorithm