Essentials of Metaheuristics
by Sean Luke
Number of pages: 233
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. The topics are short and light on examples and theory.
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by Wojciech Szpankowski - Wiley-Interscience
A book on a topic that has witnessed a surge of interest over the last decade, owing in part to several novel applications in data compression and computational molecular biology. It describes methods employed in average case analysis of algorithms.
by Anil K. Jain, Richard C. Dubes - Prentice Hall
The book is useful for scientists who gather data and seek tools for analyzing and interpreting data. It will be a reference for scientists in a variety of disciplines and can serve as a textbook for a graduate course in exploratory data analysis.
by Clifford A. Shaffer - Dover Publications
A comprehensive treatment focusing on the creation of efficient data structures and algorithms, explaining how to select the data structure best suited to specific problems. It uses Java programming language and is suitable for second-year courses.
by Clifford A. Shaffer - Virginia Tech
A comprehensive treatment of fundamental data structures and algorithm analysis with a focus on how to create efficient data structures and algorithms. Aims to help the reader gain an understanding of how to select or design the best data structure.