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008 150903s2014 xxu| o |||| 0|eng d
020 _a9781461469407
_99781461469407
024 7 _a10.1007/9781461469407
_2doi
035 _avtls000342054
039 9 _a201509030328
_bVLOAD
_c201405050238
_dVLOAD
_y201402061116
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aHD30.23
100 1 _aBurke, Edmund K.
_eeditor.
_9302421
245 1 0 _aSearch Methodologies :
_bIntroductory Tutorials in Optimization and Decision Support Techniques /
_cedited by Edmund K. Burke, Graham Kendall.
250 _a2nd ed. 2014.
264 1 _aBoston, MA :
_bSpringer US :
_bImprint: Springer,
_c2014.
300 _axiv, 716 páginas 135 ilustraciones, 15 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
500 _aSpringer eBooks
505 0 _aIntroduction -- Classical Techniques -- Integer Programming -- Genetic Algorithms -- Scatter Search -- Genetic Programming -- Artificial Immune Systems -- Swarm Intelligence -- Tabu Search -- Simulated Annealing -- GRASP: Greedy Randomized Adaptive Search Procedures -- Variable Neighborhood Search -- Very Large-Scale Neighborhood Search -- Constraint Programming -- Multi-objective Optimization -- Sharpened and Focused No Free Lunch and Complexity Theory -- Machine Learning -- Fuzzy Reasoning -- Rough-Set-Based Decision Support -- Hyper-heuristics -- Approximations and Randomization -- Fitness Landscapes.
520 _aThe first edition of Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques was originally put together to offer a basic introduction to the various search and optimization techniques that students might need to use during their research, and this new edition continues this tradition. Search Methodologies has been expanded and brought completely up to date, including new chapters covering scatter search, GRASP, and very large neighborhood search. The chapter authors are drawn from across Computer Science and Operations Research and include some of the world’s leading authorities in their field. The book provides useful guidelines for implementing the methods and frameworks described and offers valuable tutorials to students and researchers in the field. “As I embarked on the pleasant journey of reading through the chapters of this book, I became convinced that this is one of the best sources of introductory material on the search methodologies topic to be found. The book’s subtitle, “Introductory Tutorials in Optimization and Decision Support Techniques”, aptly describes its aim, and the editors and contributors to this volume have achieved this aim with remarkable success. The chapters in this book are exemplary in giving useful guidelines for implementing the methods and frameworks described.” Fred Glover, Leeds School of Business, University of Colorado Boulder, USA “[The book] aims to present a series of well written tutorials by the leading experts in their fields. Moreover, it does this by covering practically the whole possible range of topics in the discipline. It enables students and practitioners to study and appreciate the beauty and the power of some of the computational search techniques that are able to effectively navigate through search spaces that are sometimes inconceivably large. I am convinced that this second edition will build on the success of the first edition and that it will prove to be just as popular.” Jacek Blazewicz, Institute of Computing Science, Poznan University of Technology and Institute of Bioorganic Chemistry, Polish Academy of Sciences
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700 1 _aKendall, Graham.
_eeditor.
_9302422
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9781461469391
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-1-4614-6940-7
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
942 _c14
999 _c290329
_d290329