000			02789nam a22003617a 4500
003			OSt
005			20250723101103.0
008			250723b |||||||| |||| 00| 0 eng d
020			_a9783642305030 _q(hardcover)
040			_beng _cNYU _dSAIU _erda _aNYU
082			_223 _a519.6 _bG3051
245	0	0	_aHandbook of Optimization : _bFrom Classical to Modern Approach / _cIvan Zelinka, Vaclav Snasel and Ajith Abraham editors.
260			_aBerlin : _bSpringer, _c2013.
264		1	_aBerlin : _bSpringer, _c2013
264		4	_c©2013
300			_axii, 1100 pages : _billustrations color ; _c24 cm.
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
490			_aIntelligent Systems Reference Library _vVolume 38, _x1868-4394 ;
500			_aGifted by Professor Ajith Abraham
504			_aIncludes bibliographical references.
520			_aOptimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.
650		0	_aMathematical optimization _vHandbooks, manuals, etc.
650		7	_2bisacsh _aMATHEMATICS _xApplied
650		7	_2bisacsh _aMATHEMATICS _xProbability & Statistics
650		7	_2fast _aMathematical optimization
700	1		_aZelinka, Ivan _eeditor
700	1		_aSnasel, Vaclav _eeditor
700	1		_aAbraham , Ajith _eeditor
830		0	_aIntelligent systems reference library ; _v38.
942			_2ddc _cBK
999			_c6861 _d6861