000 | 01573cam a2200277Ii 4500 | ||
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001 | 9780429065026 | ||
008 | 180331s2012 flua ob 001 0 eng d | ||
020 |
_a9780429065026 _q(e-book : PDF) |
||
020 |
_z9781439868225 _q(hardback) |
||
020 |
_z9781138115248 _q(paperback) |
||
024 | 7 |
_a10.1201/b11156 _2doi |
|
035 | _a(OCoLC)759407392 | ||
050 | 4 |
_aQA402.5 _b.D43 2012 |
|
082 | 0 | 4 |
_a519.3 _bD533 |
100 | 1 |
_aDhara, Anulekha., _eauthor. _915016 |
|
245 | 1 | 0 |
_aOptimality conditions in convex optimization : _ba finite-dimensional view / _cAnulekha Dhara, Joydeep Dutta. |
264 | 1 |
_aBoca Raton, Fla. : _bCRC Press, _c2012. |
|
300 | _a1 online resource (xviii, 426 pages) | ||
504 | _aIncludes bibliographical references (pages 413-421) and index. | ||
505 | 0 | _a1. What is convex optimization? -- 2. Tools for convex optimization -- 3. Basic optimality conditions using the normal cone -- 4. Saddle points, optimality, and duality -- 5. Enhanced Fritz John optimality conditions -- 6. Optimality without constraint qualification -- 7. Sequential optimality conditions -- 8. Representation of the feasible set and KKT conditions -- 9. Weak sharp minima in convex optimization -- 10. Approximate optimality conditions -- 11. Convex semi-infinite optimization -- 12. Convexity in nonconvex optimization. | |
650 | 0 |
_aMathematical optimization. _94112 |
|
700 | 1 |
_aDutta, Joydeep. _915017 |
|
776 | 0 | 8 |
_iPrint version: _z9781439868225 _w(DLC) 2011277518 |
856 | 4 | 0 |
_uhttps://www.taylorfrancis.com/books/9781439868232 _zClick here to view. |
942 | _cEBK | ||
999 |
_c70853 _d70853 |