BONUS algorithm for large scale stochastic nonlinear programming problems /
نام عام مواد
[Book]
نام نخستين پديدآور
Urmila Diwekar, Amy David
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (xviii, 146 pages) :
ساير جزييات
illustrations (some color).
فروست
عنوان فروست
SpringerBriefs in optimization,
شاپا ي ISSN فروست
2190-8354
یادداشتهای مربوط به کتابنامه ، واژه نامه و نمایه های داخل اثر
متن يادداشت
Includes bibliographical references and index
یادداشتهای مربوط به مندرجات
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
یادداشتهای مربوط به خلاصه یا چکیده
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
ویراست دیگر از اثر در قالب دیگر رسانه
شماره استاندارد بين المللي کتاب و موسيقي
9781493922819
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Algorithms.
موضوع مستند نشده
Stochastic programming.
موضوع مستند نشده
Algorithms.
موضوع مستند نشده
Mathematics.
موضوع مستند نشده
Stochastic Processes.
مقوله موضوعی
موضوع مستند نشده
MAT-- 003000
موضوع مستند نشده
MAT-- 029000
رده بندی ديویی
شماره
519
.
7
ويراست
23
رده بندی کنگره
شماره رده
T57
.
79
سایر رده بندی ها
شماره رده
Online
Book
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )