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Books > Computing & IT > General theory of computing > Data structures
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Handbook of Approximation Algorithms and Metaheuristics, Second Edition - Two-Volume Set (Paperback, 2nd edition)
Loot Price: R3,013
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Handbook of Approximation Algorithms and Metaheuristics, Second Edition - Two-Volume Set (Paperback, 2nd edition)
Series: Chapman & Hall/CRC Computer and Information Science Series
Expected to ship within 12 - 19 working days
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Handbook of Approximation Algorithms and Metaheuristics, Second
Edition reflects the tremendous growth in the field, over the past
two decades. Through contributions from leading experts, this
handbook provides a comprehensive introduction to the underlying
theory and methodologies, as well as the various applications of
approximation algorithms and metaheuristics. Volume 1 of this
two-volume set deals primarily with methodologies and traditional
applications. It includes restriction, relaxation, local ratio,
approximation schemes, randomization, tabu search, evolutionary
computation, local search, neural networks, and other
metaheuristics. It also explores multi-objective optimization,
reoptimization, sensitivity analysis, and stability. Traditional
applications covered include: bin packing, multi-dimensional
packing, Steiner trees, traveling salesperson, scheduling, and
related problems. Volume 2 focuses on the contemporary and emerging
applications of methodologies to problems in combinatorial
optimization, computational geometry and graphs problems, as well
as in large-scale and emerging application areas. It includes
approximation algorithms and heuristics for clustering, networks
(sensor and wireless), communication, bioinformatics search,
streams, virtual communities, and more. About the Editor Teofilo F.
Gonzalez is a professor emeritus of computer science at the
University of California, Santa Barbara. He completed his Ph.D. in
1975 from the University of Minnesota. He taught at the University
of Oklahoma, the Pennsylvania State University, and the University
of Texas at Dallas, before joining the UCSB computer science
faculty in 1984. He spent sabbatical leaves at the Monterrey
Institute of Technology and Higher Education and Utrecht
University. He is known for his highly cited pioneering research in
the hardness of approximation; for his sublinear and best possible
approximation algorithm for k-tMM clustering; for introducing the
open-shop scheduling problem as well as algorithms for its solution
that have found applications in numerous research areas; as well as
for his research on problems in the areas of scheduling, graph,
computational geometry, communication, routing, etc.
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