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.
