The Design of Approximation Algorithms
by D. P. Williamson, D. B. Shmoys
Publisher: Cambridge University Press 2010
Number of pages: 496
This book shows how to design approximation algorithms: efficient algorithms that find provably near-optimal solutions. The book is organized around central algorithmic techniques for designing approximation algorithms, including greedy and local search algorithms, dynamic programming, linear and semidefinite programming, and randomization.
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by Catherine Leung - GitBook
This book is a survey of several standard algorithms and data structures. It will also introduce the methodology used to perform a formal analysis of an algorithm so that the reason behind the different implementations can be better understood.
by Jeffrey Scott Vitter - Now Publishers
The book describes several useful paradigms for the design and implementation of efficient EM algorithms and data structures. The problem domains considered include sorting, permuting, FFT, scientific computing, computational geometry, graphs, etc.
by Sean Luke
This is an open set of lecture notes on metaheuristics algorithms, intended for undergraduate students, practitioners, programmers, and other non-experts. It was developed as a series of lecture notes for an undergraduate course.
by Herbert Edelsbrunner - Duke University
The main topics to be covered in this course are: Design Techniques; Searching; Prioritizing; Graph Algorithms; Topological Algorithms; Geometric Algorithms; NP-completeness. The emphasis will be on algorithm design and on algorithm analysis.