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100301s2009 xxu| s |||| 0|eng d |
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|a 9780387719092
|9 978-0-387-71909-2
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|a 10.1007/978-0-387-71909-2
|2 doi
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|a 658.40301
|2 23
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|a Shi, Leyuan.
|e author.
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|a Nested Partitions Method, Theory and Applications
|c by Leyuan Shi, Sigurdur <U+00d3>lafsson.
|h [electronic resource] /
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| 264 |
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|a Boston, MA :
|b Springer US,
|c 2009.
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| 300 |
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|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a International Series in Operations Research & Management Science,
|v 109
|x 0884-8289 ;
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|a Introduction -- Nested partitions for deterministic optimization -- Nested partitions for stochastic optimization -- Development of stopping rules -- Hybrid nested partitions algorithms -- Applications -- Product design -- Buffer allocation -- Flexible resource scheduling -- Data mining -- Supply chain network design -- References -- Index.
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|a There is increasing need to solve large-scale complex optimization problems in a wide variety of science and engineering applications, including designing telecommunication networks for multimedia transmission, planning and scheduling problems in manufacturing and military operations, or designing nanoscale devices and systems. Advances in technology and information systems have made such optimization problems more and more complicated in terms of size and uncertainty. Nested Partitions Method, Theory and Applications provides a cutting-edge research tool to use for large-scale, complex systems optimization. The Nested Partitions (NP) framework is an innovative mix of traditional optimization methodology and probabilistic assumptions. An important feature of the NP framework is that it combines many well-known optimization techniques, including dynamic programming, mixed integer programming, genetic algorithms and tabu search, while also integrating many problem-specific local search heuristics. The book uses numerous real-world application examples, demonstrating that the resulting hybrid algorithms are much more robust and efficient than a single stand-alone heuristic or optimization technique. This book aims to provide an optimization framework with which researchers will be able to discover and develop new hybrid optimization methods for successful application of real optimization problems. Researchers and practitioners in management science, industrial engineering, economics, computer science, and environmental science will find this book valuable in their research and study. Because of its emphasis on practical applications, the book can appropriately be used as a textbook in a graduate course.
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| 650 |
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|a Economics.
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|a Computer science
|x Mathematics.
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|a Mathematical optimization.
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|a Operations research.
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|a Business logistics.
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|a Economics/Management Science.
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|a Operations Research/Decision Theory.
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|a Operations Research, Mathematical Programming.
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| 650 |
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|a Optimization.
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| 650 |
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|a Production/Logistics.
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| 650 |
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|a Computational Mathematics and Numerical Analysis.
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| 650 |
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|a Mathematical Modeling and Industrial Mathematics.
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| 700 |
1 |
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|a <U+00d3>lafsson, Sigurdur.
|e author.
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| 710 |
2 |
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|a SpringerLink (Online service)
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| 773 |
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|t Springer eBooks
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| 776 |
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|i Printed edition:
|z 9780387719085
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| 830 |
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|a International Series in Operations Research & Management Science,
|v 109
|x 0884-8289 ;
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| 856 |
4 |
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|u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-0-387-71909-2
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| 912 |
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|a ZDB-2-SBE
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| 950 |
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|a Business and Economics (Springer-11643)
|