000 03203nam a22005175i 4500
001 978-3-319-25730-3
003 DE-He213
005 20200421111654.0
007 cr nn 008mamaa
008 151026s2016 gw | s |||| 0|eng d
020 _a9783319257303
_9978-3-319-25730-3
024 7 _a10.1007/978-3-319-25730-3
_2doi
050 4 _aQA76.9.A43
072 7 _aUMB
_2bicssc
072 7 _aCOM051300
_2bisacsh
082 0 4 _a005.1
_223
100 1 _aLewis, R.M.R.
_eauthor.
245 1 2 _aA Guide to Graph Colouring
_h[electronic resource] :
_bAlgorithms and Applications /
_cby R.M.R. Lewis.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2016.
300 _aXIV, 253 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aIntroduction to Graph Colouring -- Bounds and Constructive Algorithms -- Advanced Techniques for Graph Colouring -- Algorithm Case Studies -- Applications and Extensions -- Designing Seating Plans -- Designing Sports Leagues -- Designing University Timetables -- App. A, Computing Resources -- References -- Index.
520 _aThis book treats graph colouring as an algorithmic problem, with a strong emphasis on practical applications. The author describes and analyses some of the best-known algorithms for colouring arbitrary graphs, focusing on whether these heuristics can provide optimal solutions in some cases; how they perform on graphs where the chromatic number is unknown; and whether they can produce better solutions than other algorithms for certain types of graphs, and why. The introductory chapters explain graph colouring, and bounds and constructive algorithms. The author then shows how advanced, modern techniques can be applied to classic real-world operational research problems such as seating plans, sports scheduling, and university timetabling. He includes many examples, suggestions for further reading, and historical notes, and the book is supplemented by a website with an online suite of downloadable code. The book will be of value to researchers, graduate students, and practitioners in the areas of operations research, theoretical computer science, optimization, and computational intelligence. The reader should have elementary knowledge of sets, matrices, and enumerative combinatorics.
650 0 _aComputer science.
650 0 _aOperations research.
650 0 _aDecision making.
650 0 _aAlgorithms.
650 0 _aMathematical optimization.
650 0 _aApplied mathematics.
650 0 _aEngineering mathematics.
650 1 4 _aComputer Science.
650 2 4 _aAlgorithm Analysis and Problem Complexity.
650 2 4 _aOptimization.
650 2 4 _aOperation Research/Decision Theory.
650 2 4 _aAppl.Mathematics/Computational Methods of Engineering.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319257280
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-319-25730-3
912 _aZDB-2-SCS
942 _cEBK
999 _c54572
_d54572