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008 150903s2005 gw | o |||| 0|eng d
020 _a9783540323631
_99783540323631
024 7 _a10.1007/3540323635
_2doi
035 _avtls000348337
039 9 _a201509030432
_bVLOAD
_c201404121457
_dVLOAD
_c201404091234
_dVLOAD
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_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aTA329-348
100 1 _aHart, William E.
_eeditor.
_9318695
245 1 0 _aRecent Advances in Memetic Algorithms /
_cedited by William E. Hart, J. E. Smith, N. Krasnogor.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2005.
300 _ax, 408 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 _aStudies in Fuzziness and Soft Computing,
_x1434-9922 ;
_v166
500 _aSpringer eBooks
505 0 _ato Memetic Algorithms -- Memetic Evolutionary Algorithms -- Applications of Memetic Algorithms -- An Evolutionary Approach for the Maximum Diversity Problem -- Multimeme Algorithms Using Fuzzy Logic Based Memes For Protein Structure Prediction -- A Memetic Algorithm Solving the VRP, the CARP and General Routing Problems with Nodes, Edges and Arcs -- Using Memetic Algorithms for Optimal Calibration of Automotive Internal Combustion Engines -- The Co-Evolution of Memetic Algorithms for Protein Structure Prediction -- Hybrid Evolutionary Approaches to Terminal Assignment in Communications Networks -- Effective Exploration & Exploitation of the Solution Space via Memetic Algorithms for the Circuit Partition Problem -- Methodological Aspects of Memetic Algorithms -- Towards Robust Memetic Algorithms -- NK-Fitness Landscapes and Memetic Algorithms with Greedy Operators and k-opt Local Search -- Self-Assembling of Local Searchers in Memetic Algorithms -- Designing Efficient Genetic and Evolutionary Algorithm Hybrids -- The Design of Memetic Algorithms for Scheduling and Timetabling Problems -- Memetic Algorithms for Multiobjective Optimization: Issues, Methods and Prospects -- Related Search Technologies -- A Memetic Learning Classifier System for Describing Continuous-Valued Problem Spaces -- Angels & Mortals: A New Combinatorial Optimization Algorithm.
520 _aMemetic algorithms are evolutionary algorithms that apply a local search process to refine solutions to hard problems. Memetic algorithms are the subject of intense scientific research and have been successfully applied to a multitude of real-world problems ranging from the construction of optimal university exam timetables, to the prediction of protein structures and the optimal design of space-craft trajectories. "Recent Advances in Memetic Algorithms" presents a rich state-of-the-art gallery of works on Memetic algorithms. Recent Advances in Memetic Algorithms is the first book that focuses on this technology as the central topical matter. This monograph gives a coherent, integrated view on both good practice examples and new trends including a concise and self-contained introduction to Memetic Algorithms. It is a necessary read for postgraduate students and researchers interested in recent advances in search and optimization technologies based on Memetic algorithms, but can also be used as complement to undergraduate textbooks on artificial intelligence.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aSmith, J. E.
_eeditor.
_9329192
700 1 _aKrasnogor, N.
_eeditor.
_9329193
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9783540229049
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/3-540-32363-5
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c295058
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