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 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.
by James Aspnes - Yale University
Topics include programming in C; data structures (arrays, stacks, queues, lists, trees, heaps, graphs); sorting and searching; storage allocation and management; data abstraction; programming style; testing and debugging; writing efficient programs.
by K. Mehlhorn, P. Sanders - Springer
This book is a concise introduction addressed to students and professionals familiar with programming and basic mathematical language. Individual chapters cover arrays and linked lists, hash tables and associative arrays, sorting and selection, etc.
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.