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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.
| Autorius: | Antonio J. Conejo, Ramteen Sioshansi, |
| Serija: | Springer Optimization and Its Applications |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2017 |
| Knygos puslapių skaičius: | 428 |
| ISBN-10: | 3319567675 |
| ISBN-13: | 9783319567679 |
| Formatas: | 241 x 160 x 29 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Optimization in Engineering: Models and Algorithms“
