Description: BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Author(s): Urmila Diwekar, Amy David Format: Paperback Publisher: Springer-Verlag New York Inc., United States Imprint: Springer-Verlag New York Inc. ISBN-13: 9781493922819, 978-1493922819 Synopsis This book presents the details of the BONUS algorithm and its real world applications in areas like sensor placement in large scale drinking water networks, sensor placement in advanced power systems, water management in power systems, and capacity expansion of energy systems. A generalized method for stochastic nonlinear programming based on a sampling based approach for uncertainty analysis and statistical reweighting to obtain probability information is demonstrated in this book. Stochastic optimization problems are difficult to solve since they involve dealing with optimization and uncertainty loops. There are two fundamental approaches used to solve such problems. The first being the decomposition techniques and the second method identifies problem specific structures and transforms the problem into a deterministic nonlinear programming problem. These techniques have significant limitations on either the objective function type or the underlying distributions for the uncertain variables. Moreover, these methods assume that there are a small number of scenarios to be evaluated for calculation of the probabilistic objective function and constraints. This book begins to tackle these issues by describing a generalized method for stochastic nonlinear programming problems. This title is best suited for practitioners, researchers and students in engineering, operations research, and management science who desire a complete understanding of the BONUS algorithm and its applications to the real world.
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Location: Aldershot
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Book Title: BONUS Algorithm for Large Scale Stochastic Nonlinear Programmi...
Subject Area: Data Analysis
Item Height: 235mm
Item Width: 155mm
Author: Amy David, Urmila Diwekar
Publication Name: Bonus Algorithm for Large Scale Stochastic Nonlinear Programming Problems
Format: Paperback
Language: English
Publisher: Springer-Verlag New York Inc.
Subject: Computer Science, Mathematics, Management
Publication Year: 2015
Type: Textbook
Item Weight: 2584g
Number of Pages: 146 Pages
