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001 978-3-319-67669-2
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007 cr nn 008mamaa
008 171010s2018 gw | s |||| 0|eng d
020 _a9783319676692
_9978-3-319-67669-2
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aTEC009000
_2bisacsh
072 7 _aUYQ
_2thema
082 0 4 _a006.3
_223
245 1 0 _aNature-Inspired Algorithms and Applied Optimization
_h[electronic resource] /
_cedited by Xin-She Yang.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXI, 330 p. 42 illus., 28 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aStudies in Computational Intelligence,
_x1860-949X ;
_v744
500 _aAcceso multiusuario
505 0 _aMathematical Analysis of Nature-Inspired Algorithms -- A Review of No Free Lunch Theorems, and their Implications for Metaheuristic Optimisation -- Global Convergence Analysis of Cuckoo Search Using Markov Theory -- On Effeciently Solving the Vehicle Routing Problem with Time Windows Using the Bat Algorithm -- Variants of the Flower Pollination Algorithm: A Review.
520 _aThis book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aComputational intelligence.
650 0 _aArtificial intelligence.
650 0 _aAlgorithms.
650 0 _aMathematical optimization.
650 1 4 _aComputational Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T11014
650 2 4 _aArtificial Intelligence.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I21000
650 2 4 _aAlgorithms.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M14018
650 2 4 _aOptimization.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M26008
700 1 _aYang, Xin-She.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319676685
776 0 8 _iPrinted edition:
_z9783319676708
776 0 8 _iPrinted edition:
_z9783319884653
830 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v744
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-3-319-67669-2
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
999 _c244137
_d244136