000			02074nam a22003855i 4500
001			978-3-8348-9829-6
003			DE-He213
005			20140220083819.0
007			cr nn 008mamaa
008			110128s2011 gw | s |||| 0|eng d
020			_a9783834898296 _9978-3-8348-9829-6
024	7		_a10.1007/978-3-8348-9829-6 _2doi
050		4	_aT57-57.97
072		7	_aPBW _2bicssc
072		7	_aMAT003000 _2bisacsh
082	0	4	_a519 _223
100	1		_aMahlke, Debora. _eauthor.
245	1	2	_aA Scenario Tree-Based Decomposition for Solving Multistage Stochastic Programs _h[electronic resource] : _bWith Application in Energy Production / _cby Debora Mahlke.
264		1	_aWiesbaden : _bVieweg+Teubner, _c2011.
300			_aXVI, 182p. 14 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
520			_aOptimization problems involving uncertain data arise in many areas of industrial and economic applications. Stochastic programming provides a useful framework for modeling and solving optimization problems for which a probability distribution of the unknown parameters is available. Motivated by practical optimization problems occurring in energy systems with regenerative energy supply, Debora Mahlke formulates and analyzes multistage stochastic mixed-integer models. For their solution, the author proposes a novel decomposition approach which relies on the concept of splitting the underlying scenario tree into subtrees. Based on the formulated models from energy production, the algorithm is computationally investigated and the numerical results are discussed.
650		0	_aMathematics.
650	1	4	_aMathematics.
650	2	4	_aApplications of Mathematics.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783834814098
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-8348-9829-6
912			_aZDB-2-SMA
999			_c108739 _d108739