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Record Nr. |
UNINA9910735797303321 |
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Autore |
Vagaská Alena |
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Titolo |
Optimization Methods in Mathematical Modeling of Technological Processes / / by Alena Vagaská, Miroslav Gombár, Anton Panda |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (181 pages) |
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Collana |
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Mathematical Engineering, , 2192-4740 |
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Altri autori (Persone) |
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GombárMiroslav |
PandaAnton |
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Disciplina |
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Soggetti |
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Engineering mathematics |
Engineering—Data processing |
Production engineering |
Mathematical and Computational Engineering Applications |
Process Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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1. Optimization in Historical Context -- 2. Optimization -- 3. Optimization Methods in General -- 4. Selected Methods of Multidimensional Optimization -- 5. Optimization of Technological Processes. |
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Sommario/riassunto |
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This book focuses on selected methods of applied mathematics that are aimed at mathematical optimization, with an emphasis on their application in engineering practice. It delves into the current mathematical modeling of processes and systems, with a specific focus on the optimization modeling of technological processes. The authors discuss suitable linear, convex, and nonlinear optimization methods for solving problems in engineering practice. Real-world examples and data are used to numerically illustrate the implementation of these methods, utilizing the popular MATLAB software system and its extension to convex optimization. The book covers a wide range of topics, including mathematical modeling, linear programming, convex programming, and nonlinear programming, all with an engineering optimization perspective. It serves as a comprehensive guide for |
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engineers, researchers, and students interested in the practical application of optimization methods in engineering. . |
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