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03883nam a2200601 4500 |
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978-3-319-96514-7 |
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20191220125558.0 |
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181005s2018 gw | s |||| 0|eng d |
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|a 9783319965147
|9 978-3-319-96514-7
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|a 10.1007/978-3-319-96514-7
|2 doi
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|d GrThAP
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|a QA75.5-76.95
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|a QA76.63
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|a UY
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|a COM014000
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|a 004.0151
|2 23
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|a Pillay, Nelishia.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a Hyper-Heuristics: Theory and Applications
|h [electronic resource] /
|c by Nelishia Pillay, Rong Qu.
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|a 1st ed. 2018.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2018.
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|a XVII, 130 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Natural Computing Series,
|x 1619-7127
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|a Introduction to Hyper-Heuristics -- Selection Constructive Hyper-Heuristics -- Selection Pertubative Hyper-Heuristics -- Generation Constructive Hyper-Heuristics -- Generation Perturbative Hyper-Heuristics -- Theoretical Aspect: A Formal Definition -- Vehicle Routing Problems -- Nurse Rostering Problems -- Packing Problems -- Examination Timetabling Problems -- Cross-Domain Hyper-Heuristics -- Advances in Hyper-Heuristics -- Conclusions and Future Research Directions.
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|a This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, provides an overview of selection constructive, selection perturbative, generation constructive and generation perturbative hyper-heuristics, and then a formal definition of hyper-heuristics. The chapters in the second part of the book examine applications of hyper-heuristics in vehicle routing, nurse rostering, packing and examination timetabling. The third part of the book presents advanced topics and then a summary of the field and future research directions. Finally the appendices offer details of the HyFlex framework and the EvoHyp toolkit, and then the definition, problem model and constraints for the most tested combinatorial optimization problems. The book will be of value to graduate students, researchers, and practitioners.
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650 |
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|a Computers.
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|a Computational intelligence.
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|a Artificial intelligence.
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|a Mathematical optimization.
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|a Operations research.
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|a Decision making.
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|a Theory of Computation.
|0 http://scigraph.springernature.com/things/product-market-codes/I16005
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|a Computational Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/T11014
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|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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|a Optimization.
|0 http://scigraph.springernature.com/things/product-market-codes/M26008
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650 |
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|a Operations Research/Decision Theory.
|0 http://scigraph.springernature.com/things/product-market-codes/521000
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700 |
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|a Qu, Rong.
|e author.
|4 aut
|4 http://id.loc.gov/vocabulary/relators/aut
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783319965130
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776 |
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|i Printed edition:
|z 9783319965154
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|i Printed edition:
|z 9783030072063
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|a Natural Computing Series,
|x 1619-7127
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856 |
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|u https://doi.org/10.1007/978-3-319-96514-7
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-SCS
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950 |
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|a Computer Science (Springer-11645)
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