
Categories  Free Downloadable Data Structures and Algorithms eBooks!  
Open Data Structures: An Introduction Focusing on a mathematically rigorous approach that is fast, practical, and efficient, Morin clearly and briskly presents instruction along with source code in both Java and C++. Traveling Salesman Problem, Theory and Applications This book is a collection of current research in the application of evolutionary algorithms and other optimal algorithms to solving the TSP problem. It brings together researchers with applications in Artificial Immune Systems, Genetic Algorithms, Neural Networks and Differential Evolution Algorithm. Knapsack Problems: Algorithms and Computer Implementations Here is a state of art examination on exact and approximate algorithms for a number of important NPhard problems in the field of integer linear programming, which the authors refer to as 'knapsack'. Includes not only the classical knapsack problems such as binary, bounded, unbounded or binary multiple, but also less familiar problems such as subsetsum and changemaking. Information Theory, Inference and Learning Algorithms Information theory and inference, often taught separately, are here united in one entertaining textbook. These topics lie at the heart of many exciting areas of contemporary science and engineering  communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics, and cryptography. financial engineering, and machine learning. RealWorld Applications of Genetic Algorithms The book addresses some of the most recent issues, with the theoretical and methodological aspects, of evolutionary multiobjective optimization problems and the various design challenges using different hybrid intelligent approaches. Multiobjective optimization has been available for about two decades, and its application in realworld problems is continuously increasing. Furthermore, many applications function more effectively using a hybrid systems approach. New Frontiers in Graph Theory Nowadays, graph theory is an important analysis tool in mathematics and computer science. Because of the inherent simplicity of graph theory, it can be used to model many different physical and abstract systems such as transportation and communication networks, models for business administration, political science, and psychology and so on. AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java This book illustrates how to program AI algorithms in Lisp, Prolog, and Java. The book basically cover each topic 3 times in each language. Topics include: simple productionlike system based on logic, logicbased learning, and natural language parsing. From Algorithms to ZScores: Probabilistic and Statistical Modeling in Computer Science This is a textbook for a course in mathematical probability and statistics for computer science students. Computer science examples are used throughout, in areas such as: computer networks; data and text mining; computer security; remote sensing; computer performance evaluation; software engineering; data management; etc. Search Algorithms for Engineering Optimization Heuristic Search is an important subdiscipline of optimization theory and finds applications in a vast variety of fields, including life science and engineering. Search methods have been useful in solving tough engineeringoriented problems that either could not be solved any other way or solutions take a very long time to be computed. Data Structures Succinctly, Part 2 Data Structures Succinctly Part 2 is your concise guide to skip lists, hash tables, heaps, priority queues, AVL trees, and Btrees. As with the first book, you'll learn how the structures behave, how to interact with them, and their performance limitations. Starting with skip lists and hash tables, and then moving to complex AVL trees and Btrees, author Robert Horvick explains what each structure's methods and classes are, the algorithms behind them, and what is necessary to keep them valid. Data Structures Succinctly, Part 1 Data Structures Succinctly Part 1 is your first step to a better understanding of the different types of data structures, how they behave, and how to interact with them. Starting with simple linked lists and arrays, and then moving to more complex structures like binary search trees and sets, author Robert Horvick explains what each structure's methods and classes are and the algorithms behind them. 
