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Books > Business & Economics > Business & management > Management of specific areas > Production & quality control management
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Scheduling: Control-Based Theory and Polynomial-Time Algorithms (Hardcover, 2000 ed.)
Loot Price: R4,230
Discovery Miles 42 300
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Scheduling: Control-Based Theory and Polynomial-Time Algorithms (Hardcover, 2000 ed.)
Series: Applied Optimization, 43
Expected to ship within 18 - 22 working days
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This book presents a first attempt to systematically collect,
classify and solve various continuous-time scheduling problems. The
classes of problems distinguish scheduling by the number of
machines and products, production constraints and performance
measures. Although such classes are usually considered to be a
prerogative of only combinatorial scheduling literature, the
scheduling methodology suggested in this book is based on two
mathematical tools - optimal control and combinatorics. Generally
considered as belonging to two totally different areas of research
and application, these seemingly irreconcilable tools can be
integrated in a unique solution approach with the advantages of
both. This new approach provides the possibility of developing
effective polynomial-time algorithms to solve the generic
scheduling problems. This book is aimed at a student audience -
final year undergraduates as well as master and Ph.D. students,
primarily in Operations Research, Management, Industrial
Engineering and Control Systems. Indeed, some of the material in
the book has formed part of the content of undergraduate and
graduate courses taught at the Industrial Engineering Department of
Tel-Aviv University, the Logistics Department of Bar-Ilan
University and the Technology Management Department of Rolon Center
for Technological Education, Israel. The book is also useful for
practicing engineers interested in planning, scheduling and
optimization methods. Since the book addresses the theory and
design of computer-based scheduling algorithms, applied
mathematicians and computer software specialists engaged in
developing scheduling software for industrial engineering and
management problems will find that the methods developed here can
be embedded very efficiently in large applications.
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