000			03526nam a22005655i 4500
001			978-1-4614-8042-6
003			DE-He213
005			20140220082831.0
007			cr nn 008mamaa
008			130805s2013 xxu| s |||| 0|eng d
020			_a9781461480426 _9978-1-4614-8042-6
024	7		_a10.1007/978-1-4614-8042-6 _2doi
050		4	_aQA613-613.8
050		4	_aQA613.6-613.66
072		7	_aPBMS _2bicssc
072		7	_aPBPH _2bicssc
072		7	_aMAT038000 _2bisacsh
082	0	4	_a514.34 _223
100	1		_aSergeyev, Yaroslav D. _eauthor.
245	1	0	_aIntroduction to Global Optimization Exploiting Space-Filling Curves _h[electronic resource] / _cby Yaroslav D. Sergeyev, Roman G. Strongin, Daniela Lera.
264		1	_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013.
300			_aX, 125 p. 32 illus., 30 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringerBriefs in Optimization, _x2190-8354
505	0		_a 1. Introduction -- 2. Approximations to Peano curves -- 3. Global optimization algorithms using curves to reduce dimensionality of the problem -- 4. Ideas for acceleration -- 5. A brief conclusion -- References.
520			_aIntroduction to Global Optimization Exploiting Space-Filling Curves provides an overview of classical and new results pertaining to the usage of space-filling curves in global optimization.  The authors look at a family of derivative-free numerical algorithms applying space-filling curves to reduce the dimensionality of the global optimization problem; along with a number of unconventional ideas, such as adaptive strategies for estimating Lipschitz constant, balancing global and local information to accelerate the search. Convergence conditions of the described algorithms are studied in depth and theoretical considerations are illustrated through numerical examples. This work also contains a code for implementing space-filling curves that can be used for constructing new global optimization algorithms. Basic ideas from this text can be applied to a number of problems including problems with multiextremal and partially defined constraints and non-redundant parallel computations can be organized. Professors, students, researchers, engineers, and other professionals in the fields of pure mathematics, nonlinear sciences studying fractals, operations research, management science, industrial and applied mathematics, computer science, engineering, economics, and the environmental sciences will find this title useful .
650		0	_aMathematics.
650		0	_aGeometry, algebraic.
650		0	_aComputer software.
650		0	_aNumerical analysis.
650		0	_aCell aggregation _xMathematics.
650	1	4	_aMathematics.
650	2	4	_aManifolds and Cell Complexes (incl. Diff.Topology).
650	2	4	_aOperations Research, Management Science.
650	2	4	_aMathematical Software.
650	2	4	_aNumerical Analysis.
650	2	4	_aAlgebraic Geometry.
700	1		_aStrongin, Roman G. _eauthor.
700	1		_aLera, Daniela. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781461480419
830		0	_aSpringerBriefs in Optimization, _x2190-8354
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4614-8042-6
912			_aZDB-2-SMA
999			_c96023 _d96023