000 03994nam a22005895i 4500
001 978-3-319-44254-9
003 DE-He213
005 20210118143635.0
007 cr nn 008mamaa
008 160922s2017 gw | s |||| 0|eng d
020 _a9783319442549
_9978-3-319-44254-9
024 7 _a10.1007/978-3-319-44254-9
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
100 1 _aKulkarni, Anand Jayant.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aCohort Intelligence: A Socio-inspired Optimization Method
_h[electronic resource] /
_cby Anand Jayant Kulkarni, Ganesh Krishnasamy, Ajith Abraham.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXI, 134 p. 29 illus.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v114
505 0 _aIntroduction To Optimization -- Socio-Inspired Optimization Using Cohort Intelligence -- Cohort Intelligence For Constrained Test Problems -- Modified Cohort Intelligence For Solving Machine Learning Problems -- Solution To 0-1 Knapsack Problem Using Cohort Intelligence Algorithm -- Cohort Intelligence For Solving Travelling Salesman Problems -- Solution To A New Variant Of The Assignment Problem Using Cohort Intelligence Algorithm -- Solution To Sea Cargo Mix (Scm) Problem Using Cohort Intelligence Algorithm -- Solution To The Selection Of Cross-Border Shippers (Scbs) Problem -- Conclusions And Future Directions.
520 _aThis Volume discusses the underlying principles and analysis of the different concepts associated with an emerging socio-inspired optimization tool referred to as Cohort Intelligence (CI). CI algorithms have been coded in Matlab and are freely available from the link provided inside the book. The book demonstrates the ability of CI methodology for solving combinatorial problems such as Traveling Salesman Problem and Knapsack Problem in addition to real world applications from the healthcare, inventory, supply chain optimization and Cross-Border transportation. The inherent ability of handling constraints based on probability distribution is also revealed and proved using these problems. .
650 0 _aComputational intelligence.
650 0 _aArtificial intelligence.
650 1 4 _aComputational Intelligence.
_0http://scigraph.springernature.com/things/product-market-codes/T11014
650 2 4 _aArtificial Intelligence.
_0http://scigraph.springernature.com/things/product-market-codes/I21000
700 1 _aKrishnasamy, Ganesh.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
700 1 _aAbraham, Ajith.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783319442532
776 0 8 _iPrinted edition:
_z9783319442556
776 0 8 _iPrinted edition:
_z9783319830223
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v114
856 4 0 _uhttps://doi.org/10.1007/978-3-319-44254-9
912 _aZDB-2-ENG
999 _c451219
_d451219
942 _cEB
506 _aAvailable to subscribing member institutions only. Доступно лише організаціям членам підписки.
506 _fOnline access from local network of NaUOA.
506 _fOnline access with authorization at https://link.springer.com/
506 _fОнлайн-доступ з локальної мережі НаУОА.
506 _fОнлайн доступ з авторизацією на https://link.springer.com/