Optimization in Engineering
Models and Algorithms| By: | Ramteen Sioshansi; Antonio J. Conejo |
| Publisher: | Springer Nature |
| Print ISBN: | 9783319567679 |
| eText ISBN: | 9783319567693 |
| Edition: | 0 |
| Copyright: | 2017 |
| Format: | Reflowable |
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This textbook covers the fundamentals of optimization, including linear, mixed-integer linear, nonlinear, and dynamic optimization techniques, with a clear engineering focus. It carefully describes classical optimization models and algorithms using an engineering problem-solving perspective, and emphasizes modeling issues using many real-world examples related to a variety of application areas. Providing an appropriate blend of practical applications and optimization theory makes the text useful to both practitioners and students, and gives the reader a good sense of the power of optimization and the potential difficulties in applying optimization to modeling real-world systems. The book is intended for undergraduate and graduate-level teaching in industrial engineering and other engineering specialties. It is also of use to industry practitioners, due to the inclusion of real-world applications, opening the door to advanced courses on both modeling and algorithm development within the industrial engineering and operations research fields.