Algorithmic design, especially for hard problems, is more essential for success in solving them than any standard improvement of current computer technologies. Because of this, the design of algorithms for solving hard problems is the core of current algorithmic research from the theoretical point of view as weIl as from the practical point of view. There are many general textbooks on algorithmics, and several specialized books devoted to particular approaches such as local search, randomization, approximation algorithms, or heuristics. But there is no textbook that focuses on the design of algorithms for hard computing tasks, and that systematically explains, combines, and compares the main possibilities for attacking hard algorithmic problems. As this topic is fundamental for computer science, this book tries to elose this gap. Another motivation, and probably the main reason for writing this book, is connected to education. The considered area has developed very dynamically in recent years and the research on this topic discovered several profound re sults, new concepts, and new methods. Some of the achieved contributions are so fundamental that one can speak about paradigms which should be ineluded in the education of every computer science student. Unfortunately, this is very far from reality. This is because these paradigms are not sufficiently known in the computer science community, and so they are insufficiently communicated to students and practitioners.
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This book is an introduction to the methods of designing algorithms for hard computing tasks. This area has developed very dynamically in the last years and is one of the kernels of current research in algorithm and complexity theory.
The book mainly concentrates on approximate, randomized and heuristic algorithms, and on the theoretical and experimental comparison of these approaches according to the requirements of the practice. There exist several monographs specializing in some of these methods, but no book systematically explains and compares all main possibilities of attacking hard computing problems. Since the topic is fundamental for the university study in computer science and essential for the transfer of formal methods to the practice, the aim of the book is to close this gap by providing at once a textbook for graduate students and a handbook for practitioners dealing with hard computing problems.
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