Algorithms Illuminated Part 4 Algorithms for NP Hard Problems 3rd Edition by Tim Roughgarden ISBN 9780999282960
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ISBN 13: 9780999282960
Author: Tim Roughgarden
Fourth book in a series that provides an accessible, no-nonsense, and programming language-agnostic introduction to algorithms. Includes hints of solutions to all quizzes and problems, and a series of YouTube videos by the author accompanies the book. Part 4 covers algorithmic tools for tackling NP-hard problems (heuristic algorithms, local search, dynamic programming, MIP and SAT solvers) and techniques for quickly recognizing NP-hard problems in the wild.
Table of contents:
Chapter 19: What Is NP-Hardness?
19.1 MST vs. TSP: An Algorithmic Mystery
19.2 Possible Levels of Expertise
19.3 Easy and Hard Problems
19.4 Algorithmic Strategies for NP-Hard Problems
19.5 Proving NP-Hardness: A Simple Recipe
19.6 Rookie Mistakes and Acceptable Inaccuracies
Problems
Chapter 20: Compromising on Correctness: Efficient Inexact Algorithms
20.1 Makespan Minimization
20.2 Maximum Coverage
*20.3 Influence Maximization
20.4 The 2-OPT Heuristic Algorithm for the TSP
20.5 Principles of Local Search
Problems
Chapter 21: Compromising on Speed: Exact Inefficient Algorithms
21.1 The Bellman-Held-Karp Algorithm for the TSP
*21.2 Finding Long Paths by Color Coding
21.3 Problem-Specific Algorithms vs. Magic Boxes
21.4 Mixed Integer Programming Solvers
21.5 Satisfiability Solvers
Problems
Chapter 22: Proving Problems NP-Hard
22.1 Reductions Revisited
22.2 3-SAT and the Cook-Levin Theorem
22.3 The Big Picture
22.4 A Template for Reductions
22.5 Independent Set Is NP-Hard
*22.6 Directed Hamiltonian Path Is NP-Hard
22.7 The TSP Is NP-Hard
22.8 Subset Sum Is NP-Hard
Problems
Chapter 23: P, NP, and All That
*23.1 Amassing Evidence of Intractability
*23.2 Decision, Search, and Optimization
*23.3 NP: Problems with Easily Recognized Solutions
*23.4 The P ≠ NP Conjecture
*23.5 The Exponential Time Hypothesis
*23.6 NP-Completeness
Problems
Chapter 24: Case Study: The FCC Incentive Auction
24.1 Repurposing Wireless Spectrum
24.2 Greedy Heuristics for Buying Back Licenses
24.3 Feasibility Checking
24.4 Implementation as a Descending Clock Auction
24.5 The Final Outcome
Problems
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Tim Roughgarden,Algorithms,Hard