عنوان

BONUS algorithm for large scale stochastic nonlinear programming problems /

شابک

1493922815

شابک

1493922823

شابک

9781493922819

شابک

9781493922826

شابک اشتباه

9781493922819

شماره

dltt

عنوان اصلي

BONUS algorithm for large scale stochastic nonlinear programming problems /

نام عام مواد

[Book]

نام نخستين پديدآور

Urmila Diwekar, Amy David

نام خاص و کميت اثر

1 online resource (xviii, 146 pages) :

ساير جزييات

illustrations (some color).

عنوان فروست

SpringerBriefs in optimization,

شاپا ي ISSN فروست

2190-8354

متن يادداشت

Includes bibliographical references and index

متن يادداشت

1. Introduction -- 2. Uncertainty Analysis and Sampling Techniques -- 3. Probability Density Functions and Kernel Density Estimation -- 4. The BONUS Algorithm -- 5. Water Management under Weather Uncertainty -- 6. Real Time Optimization for Water Management -- 7. Sensor Placement under Uncertainty for Power Plants -- 8. The L-Shaped BONUS Algorithm -- 9. The Environmental Trading Problem -- 10. Water Security Networks -- References -- Index

بدون عنوان

0

متن يادداشت

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

شماره استاندارد بين المللي کتاب و موسيقي

9781493922819

موضوع مستند نشده

Algorithms.

موضوع مستند نشده

Stochastic programming.

موضوع مستند نشده

Algorithms.

موضوع مستند نشده

Mathematics.

موضوع مستند نشده

Stochastic Processes.

موضوع مستند نشده

MAT-- 003000

موضوع مستند نشده

MAT-- 029000

شماره

ويراست

شماره رده

شماره رده

مستند نام اشخاص تاييد نشده

Diwekar, Urmila M.

مستند نام اشخاص تاييد نشده

David, Amy

مستند نام تنالگان تاييد نشده

Ohio Library and Information Network.

تاريخ عمليات

20161014100150.2

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y