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The fields of computer science and optimization greatly influence each other, and this book is about one important connection between the two: complexity theory. Complexity theory underlies computer algorithms and is used to address such questions as the efficiency of algorithms and the possibility of algorithmic solutions for particular problems. Furthermore, as optimization problems increase in size with hardware capacity, complexity theory plays a steadily growing role in the exploration of optimization algorithms. As larger and more complicated problems are addressed, it is more important than ever to understand the asymptotic complexity issues. This book describes some of the key developments in the complexity aspects of optimization during the last decade. It will be a valuable source of information for computer scientists and computational mathematicians.
This book investigates the intersection of complexity theory and nonlinear optimization to determine the efficiency and solvability of computational algorithms. Stephen A. Vavasis, a researcher in computational mathematics, provides a rigorous examination of how complexity theory informs the development of optimization algorithms as problem scales increase. The text synthesizes developments from the late 20th century to establish a framework for understanding the asymptotic behavior of these mathematical models.
What You Will Find
Experts recognize this work as a specialized reference for researchers in computational mathematics and theoretical computer science. Readers frequently note the high level of mathematical rigor and the density of the technical prose throughout the chapters.
Page Count:
184
Publication Date:
1991-10-17
Publisher:
Oxford University Press
ISBN-10:
0195072081
ISBN-13:
9780195072082
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