000			03050nam a22003617a 4500
003			OSt
005			20250707161626.0
008			250707b |||||||| |||| 00| 0 eng d
020			_a9783642010842 _q(hardcover)
040			_beng _cDLC _dDLC _erda _aSai University Library
082			_223 _a519.6 _bABR
245	0	0	_aFoundations of computational intelligence _cAjith Abraham, Aboul-Ella Hassanien, Patrick Siarry, Andries Engelbrecht editors _nVolume 3, _pGlobal optimization /
260			_aBerlin ; _bSpringer, _c2009
264		1	_aBerlin ; _bSpringer, _c2009
264		4	_c©2009
300			_axii, 526 pages : _billustrations ; _c25 cm
336			_2rdacontent _atext _btxt
337			_2rdamedia _aunmediated _bn
338			_2rdacarrier _avolume _bnc
490			_a Foundations of computational intelligence _vv. 203
500			_aGifted by Professor Ajith Abraham
504			_aIncludes bibliographical references and index
520			_aAnnotation Global optimization is a branch of applied mathematics and numerical analysis that deals with the task of finding the absolutely best set of admissible conditions to satisfy certain criteria / objective function(s), formulated in mathematical terms. Global optimization includes nonlinear, stochastic and combinatorial programming, multiobjective programming, control, games, geometry, approximation, algorithms for parallel architectures and so on. Due to its wide usage and applications, it has gained the attention of researchers and practitioners from a plethora of scientific domains. Typical practical examples of global optimization applications include: Traveling salesman problem and electrical circuit design (minimize the path length); safety engineering (building and mechanical structures); mathematical problems (Kepler conjecture); Protein structure prediction (minimize the energy function) etc. Global Optimization algorithms may be categorized into several types: Deterministic (example: branch and bound methods), Stochastic optimization (example: simulated annealing). Heuristics and meta-heuristics (example: evolutionary algorithms) etc. Recently there has been a growing interest in combining global and local search strategies to solve more complicated optimization problems. This edited volume comprises 17 chapters, including several overview Chapters, which provides an up-to-date and state-of-the art research covering the theory and algorithms of global optimization. Besides research articles and expository papers on theory and algorithms of global optimization, papers on numerical experiments and on real world applications were also encouraged. The book is divided into 2 main parts
650		0	_aArtificial intelligence
650		0	_aComputational intelligence
650		0	_aMathematical optimization
700	1		_eeditor _aAbraham, Ajith
700	1		_aHassanien, Aboul-Ella _eeditor
700	1		_aSiarry, Patrick _eeditor
700	1		_aEngelbrecht, Andries _eeditor
830			_aStudies in Computational Intelligence _vv. 203.
942			_2ddc _cBK
999			_c6837 _d6837