BONUS Algorithm for Large Scale Stochastic Nonlinear Programming Problems
Stochastic programming problems are very difficult to solve as they involve optimization as well as uncertainty analysis. Algorithms for solving large-scale nonlinear stochastic programming problems are very few in number, as are the engineering applications of these problems. This book introduce...
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| Những tác giả chính: | , |
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| Định dạng: | Sách |
| Ngôn ngữ: | English |
| Được phát hành: |
Springer
2015
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| Những chủ đề: | |
| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57248 |
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| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
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| Tóm tắt: | Stochastic programming problems are very difficult to solve as they involve
optimization as well as uncertainty analysis. Algorithms for solving large-scale
nonlinear stochastic programming problems are very few in number, as are the
engineering applications of these problems. This book introduces two algorithms for
large-scale stochastic nonlinear problems for both open equation systems and black
box models. These algorithms are the Better Optimization of Nonlinear Uncertain
Systems (BONUS) algorithm and the L-shaped BONUS algorithm. Real-world ap
plications of these algorithms in the areas of energy and environmental engineering
are also detailed. Many have contributed to this book. Researchers who worked
with Dr. Diwekar including Dr. Adrian Lee, Dr. Kemal Sahin, Dr. Juan Salazar,
and Dr. Yogendra Shastri, as well as collaborators such as Dr. Emil Constantinescu,
Dr. Victor Zavala, and Dr. Stephen Zitney have provided the material for this book
with their research. Thanks also to our group members Dr. Pahola Benavides, Dr.
Berhane Gabreslassie, Dr. Rajib Mukherjee, Shivam Tyagi, and Kirti Yenki who
went through the first draft of the book and meticulously pointed out mistakes. Hope
you enjoy this work... |
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