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 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 John Morris
The text focuses on data structures and algorithms for manipulating them. Data structures for storing information in tables, lists, trees, queues and stacks are covered. Some basic graph and discrete transform algorithms are also discussed.
by Albert Nijenhuis, Herbert S. Wilf - Academic Press Inc
This is a collection of mathematical algorithms with many new and interesting examples in this second edition. The authors tried to place in the reader's hands a kit of building blocks with which the reader can construct more elaborate structures.
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.