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| 001 | 978-3-031-02406-1 | ||
| 003 | DE-He213 | ||
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| 007 | cr nn 008mamaa | ||
| 008 | 220601s2014 sz | s |||| 0|eng d | ||
| 020 |
_a9783031024061 _9978-3-031-02406-1 |
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| 024 | 7 |
_a10.1007/978-3-031-02406-1 _2doi |
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| 100 | 1 |
_aMordukhovich, Boris S. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981213 |
|
| 245 | 1 | 3 |
_aAn Easy Path to Convex Analysis and Applications _h[electronic resource] / _cby Boris S. Mordukhovich, Nguyen Mau Nam. |
| 250 | _a1st ed. 2014. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014. |
|
| 300 |
_aXVI, 202 p. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aSynthesis Lectures on Mathematics & Statistics, _x1938-1751 |
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| 505 | 0 | _aPreface -- Acknowledgments -- List of Symbols -- Convex Sets and Functions -- Subdifferential Calculus -- Remarkable Consequences of Convexity -- Applications to Optimization and Location Problems -- Solutions and Hints for Exercises -- Bibliography -- Authors' Biographies -- Index . | |
| 520 | _aConvex optimization has an increasing impact on many areas of mathematics, applied sciences, and practical applications. It is now being taught at many universities and being used by researchers of different fields. As convex analysis is the mathematical foundation for convex optimization, having deep knowledge of convex analysis helps students and researchers apply its tools more effectively. The main goal of this book is to provide an easy access to the most fundamental parts of convex analysis and its applications to optimization. Modern techniques of variational analysis are employed to clarify and simplify some basic proofs in convex analysis and build the theory of generalized differentiation for convex functions and sets in finite dimensions. We also present new applications of convex analysis to location problems in connection with many interesting geometric problems such as the Fermat-Torricelli problem, the Heron problem, the Sylvester problem, and their generalizations. Of course, we do not expect to touch every aspect of convex analysis, but the book consists of sufficient material for a first course on this subject. It can also serve as supplemental reading material for a course on convex optimization and applications. | ||
| 650 | 0 |
_aMathematics. _911584 |
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_aStatistics . _931616 |
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_aEngineering mathematics. _93254 |
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_aMathematics. _911584 |
| 650 | 2 | 4 |
_aStatistics. _914134 |
| 650 | 2 | 4 |
_aEngineering Mathematics. _93254 |
| 700 | 1 |
_aMau Nam, Nguyen. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981214 |
|
| 710 | 2 |
_aSpringerLink (Online service) _981215 |
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| 773 | 0 | _tSpringer Nature eBook | |
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_iPrinted edition: _z9783031012785 |
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_iPrinted edition: _z9783031035340 |
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_aSynthesis Lectures on Mathematics & Statistics, _x1938-1751 _981216 |
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