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Optimization in engineering: models and algorithms
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 emp...
Autores principales: | , |
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Lenguaje: | eng |
Publicado: |
Springer
2017
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-56769-3 http://cds.cern.ch/record/2272811 |
_version_ | 1780954944325550080 |
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author | Sioshansi, Ramteen Conejo, Antonio J |
author_facet | Sioshansi, Ramteen Conejo, Antonio J |
author_sort | Sioshansi, Ramteen |
collection | CERN |
description | 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. |
id | cern-2272811 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2017 |
publisher | Springer |
record_format | invenio |
spelling | cern-22728112021-04-21T19:09:18Zdoi:10.1007/978-3-319-56769-3http://cds.cern.ch/record/2272811engSioshansi, RamteenConejo, Antonio JOptimization in engineering: models and algorithmsMathematical Physics and MathematicsThis 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.Springeroai:cds.cern.ch:22728112017 |
spellingShingle | Mathematical Physics and Mathematics Sioshansi, Ramteen Conejo, Antonio J Optimization in engineering: models and algorithms |
title | Optimization in engineering: models and algorithms |
title_full | Optimization in engineering: models and algorithms |
title_fullStr | Optimization in engineering: models and algorithms |
title_full_unstemmed | Optimization in engineering: models and algorithms |
title_short | Optimization in engineering: models and algorithms |
title_sort | optimization in engineering: models and algorithms |
topic | Mathematical Physics and Mathematics |
url | https://dx.doi.org/10.1007/978-3-319-56769-3 http://cds.cern.ch/record/2272811 |
work_keys_str_mv | AT sioshansiramteen optimizationinengineeringmodelsandalgorithms AT conejoantonioj optimizationinengineeringmodelsandalgorithms |