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001			303360
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008			150903s2010 gw | o |||| 0|eng d
020			_a9783642165443 _99783642165443
024	7		_a10.1007/9783642165443 _2doi
035			_avtls000356039
039		9	_a201509030945 _bVLOAD _c201405060359 _dVLOAD _y201402191209 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQA76.9.A43
100	1		_aNeumann, Frank. _eautor _9341915
245	1	0	_aBioinspired Computation in Combinatorial Optimization : _bAlgorithms and Their Computational Complexity / _cby Frank Neumann, Carsten Witt.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_axii, 216 páginas _brecurso en línea.
336			_atexto _btxt _2rdacontent
337			_acomputadora _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_aarchivo de texto _bPDF _2rda
490	0		_aNatural Computing Series, _x1619-7127
500			_aSpringer eBooks
505	0		_aBasics -- Combinatorial Optimization and Computational Complexity -- Stochastic Search Algorithms -- Analyzing Stochastic Search Algorithms -- Single-objective Optimization -- Minimum Spanning Trees -- Maximum Matchings -- Makespan Scheduling -- Shortest Paths -- Eulerian Cycles -- Multi-objective Optimization -- Multi-objective Minimum Spanning Trees -- Minimum Spanning Trees Made Easier -- Covering Problems -- Cutting Problems.
520			_aBioinspired computation methods, such as evolutionary algorithms and ant colony optimization, are being applied successfully to complex engineering and combinatorial optimization problems, and it is very important that we understand the computational complexity of these search heuristics. This is the first book to explain the most important results achieved in this area. The authors show how runtime behavior can be analyzed in a rigorous way. in particular for combinatorial optimization. They present well-known problems such as minimum spanning trees, shortest paths, maximum matching, and covering and scheduling problems. Classical single-objective optimization is examined first. They then investigate the computational complexity of bioinspired computation applied to multiobjective variants of the considered combinatorial optimization problems, and in particular they show how multiobjective optimization can help to speed up bioinspired computation for single-objective optimization problems. This book will be valuable for graduate and advanced undergraduate courses on bioinspired computation, as it offers clear assessments of the benefits and drawbacks of various methods. It offers a self-contained presentation, theoretical foundations of the techniques, a unified framework for analysis, and explanations of common proof techniques, so it can also be used as a reference for researchers in the areas of natural computing, optimization and computational complexity.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aWitt, Carsten. _eautor _9341916
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783642165436
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-16544-3 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999			_c303360 _d303360