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Mathematics | Nested Partitions Method, Theory and Applications

Nested Partitions Method, Theory and Applications

Shi, Leyuan, Ólafsson, Sigurdur

2009, X, 260 p.

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  • Nested Partitions (NP) framework combines well-known optimization techniques with problem-specific local search heuristics for increased effectiveness
  • Emphasizes the solution of real-world problems in a broad range of areas, from telecommunications to manufacturing and military operations and design of nanoscale systems

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.

 

Content Level » Research

Keywords » Manufacturing - Multimedia - Scheduling - Stochastic Optimization - algorithm - algorithms - combinatorial optimization - communication - complex systems - data mining - genetic algorithms - meta-heuristics - mixed integer programming - optimization - programming

Related subjects » Applications - Computational Science & Engineering - Mathematics - Operations Research & Decision Theory - Production & Logistics

Table of contents 

Methodology.- The Nested Partitions Method.- Noisy Objective Functions.- Mathematical Programming in the NP Framework.- Hybrid Nested Partitions Algorithm.- Applications.- Flexible Resource Scheduling.- Feature Selection.- Supply Chain Network Design.- Beam Angle Selection.- Local Pickup and Delivery Problem.- Extended Job Shop Scheduling.- Resource Allocation under Uncertainty.

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