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80.6 MB
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7FDB3113E4C36055BDEE58A555A30EC1E4E56759
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Jan. 10, 2026, 3:30 p.m.
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(Last updated: Jan. 10, 2026, 3:38 p.m.)
| File | Size |
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| Giron-Sierra J. Introduction to Optimization with MatLAB Examples 2026.pdf | 80.6 MB |
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SOURCE: Giron-Sierra J. Introduction to Optimization with MatLAB Examples 2026
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MEDIAINFO
Textbook in PDF format The textbook provides a comprehensive yet practical look at optimization theory and applications, with examples and MatLAB programs. The author introduces concepts and methods with mathematical formulations followed by clear examples. The programs provided in MatLAB, inserted in text (being also downloadable), are useful for practicing the methods on the given examples, and for visualization of results. Topics covered include Linear Programming or Calculus of Variations, Quadratic Programming, Integer Programming, etc. After presenting basics, the book goes on to introduce further methodological steps, like Interior Point methods, Evolutionary approaches, Multi-objective Optimization and Decision-making (including Portfolio management), Games, and the application to sparse representations (also related to Machine Learning) and image processing. The reader can easily take initiative, exploring other examples or cases of own interest, by using/modifying the programs. The book is addressed to upper undergraduate and graduate students of engineering, mathematics and other sciences, computer studies, economics, and management. Preface. Fundamental Aspects of Optimization. Searching Methods. Linear Programming. Classic Analytical Methods. Methods for Dynamic Optimization: Dynamic Programming and Pontryagin Method. Optimal Control. Quadratic Programming. Integer Programming. Convex Programming. Interior Point Methodology. Evolutionary Optimization: Introduction. Evolutionary Optimization: Bio-inspired Methods. Evolutionary Optimization: Other Metaphors. Multi-Objective Optimization. Duality, Games, and Proximal Methods. Applications in Image and Data Processing. A Long Programs
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