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04170nam a22005175i 4500 |
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978-3-642-39304-4 |
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20210615231432.0 |
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130712s2013 gw | s |||| 0|eng d |
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|a 9783642393044
|9 978-3-642-39304-4
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|a 10.1007/978-3-642-39304-4
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|a Q342
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|a 006.3
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|a Automated Scheduling and Planning
|h [electronic resource] :
|b From Theory to Practice /
|c edited by A. Sima Uyar, Ender Ozcan, Neil Urquhart.
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|a 1st ed. 2013.
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg :
|b Imprint: Springer,
|c 2013.
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|a XVI, 304 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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|a online resource
|b cr
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|a text file
|b PDF
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 505
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|a Airport Airside Optimisation Problems(Atkin) -- Instruction Scheduling in Microprocessors(Kucuk Guney and Ponomarev) -- Sports Scheduling: Minimizing Travel for English Football Supporters (Kendall and Westphal) -- Educational Timetabling (Kingston) -- Automated Shift Design and Break Scheduling (Gaspero, Gartner, Musliu, Schaerf,Schafhauser, and Slany) -- Nurse Rostering: a Complex Example of Personnel Scheduling with Perspectives (Smet, Causmaecker, Bilgin and Vanden Berghe) -- Radiotherapy Scheduling (Petrovic, Castro, Petrovic and Kapamara) -- Recent Advances in Evolutionary Algorithms for Job Shop Scheduling (Akay and Yao) -- Multi-objective Grid Scheduling (Arsuaga-Rios and Vega-Rodriguez) -- A Dynamic Multi-objective Job Shop Scheduling: A Genetic Programming Approach (Nguyen, Zhang, Johnston, and Tan) -- Dynamic Vehicle Routing: A Memetic Ant Colony Optimization approach (Michalis Mavrovouniotis and Shengxiang Yang).
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|a Solving scheduling problems has long presented a challenge for computer scientists and operations researchers. The field continues to expand as researchers and practitioners examine ever more challenging problems and develop automated methods capable of solving them. This book provides 11 case studies in automated scheduling, submitted by leading researchers from across the world. Each case study examines a challenging real-world problem by analysing the problem in detail before investigating how the problem may be solved using state of the art techniques.The areas covered include aircraft scheduling, microprocessor instruction scheduling, sports fixture scheduling, exam scheduling, personnel scheduling and production scheduling. Problem solving methodologies covered include exact as well as (meta)heuristic approaches, such as local search techniques, linear programming, genetic algorithms and ant colony optimisation.The field of automated scheduling has the potential to impact many aspects of our lives and work; this book highlights contributions to the field by world class researchers. .
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|a Computational intelligence.
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|a Artificial intelligence.
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|a Computational Intelligence.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/T11014
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|a Artificial Intelligence.
|0 https://scigraph.springernature.com/ontologies/product-market-codes/I21000
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|a Uyar, A. Sima.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Ozcan, Ender.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a Urquhart, Neil.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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|a SpringerLink (Online service)
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|t Springer Nature eBook
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|i Printed edition:
|z 9783642393051
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|i Printed edition:
|z 9783642435966
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|i Printed edition:
|z 9783642393037
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|a Studies in Computational Intelligence,
|x 1860-949X ;
|v 505
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|u https://doi.org/10.1007/978-3-642-39304-4
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|a ZDB-2-ENG
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|a ZDB-2-SXE
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|a Engineering (SpringerNature-11647)
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|a Engineering (R0) (SpringerNature-43712)
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