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 David M. Mount - University of Maryland
The focus is on how to design good algorithms, and how to analyze their efficiency. The text covers some preliminary material, optimization algorithms, graph algorithms, minimum spanning trees, shortest paths, network flows and computational geometry.
by Niklaus Wirth - Prentice Hall
The book treats practically important algorithms and data structures. It starts with a chapter on data structure, then it treats sorting algorithms, concentrates on several examples of recursion, and deals with dynamic data structures.
by Ian Craw, John Pulham - University of Aberdeen
This course studies computer algorithms, their construction, validation and effectiveness. A number of topics will be covered: a general introduction to the subject, the problem of sorting data sets into order, the theory of formal grammars, etc.
by Wolfgang Merkle - ESSLLI
The first part of the course gives an introduction to randomized algorithms and to standard techniques for their derandomization. The second part presents applications of the probabilistic method to the construction of logical models.