國立虎尾科技大學 |

Nature-Inspired Algorithms and Applied Optimization

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Nature-Inspired Algorithms and Applied Optimization/ edited by Xin-She Yang.
其他作者:	Yang, Xin-She.
面頁冊數:	XI, 330 p. 42 illus., 28 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Computational intelligence. -
電子資源:	https://doi.org/10.1007/978-3-319-67669-2
ISBN:	9783319676692

Nature-Inspired Algorithms and Applied Optimization
Nature-Inspired Algorithms and Applied Optimization[electronic resource] /edited by Xin-She Yang. - 1st ed. 2018. - XI, 330 p. 42 illus., 28 illus. in color.online resource. - Studies in Computational Intelligence,7441860-949X ;. - Studies in Computational Intelligence,564.

Mathematical 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.

This 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.

ISBN: 9783319676692

Standard No.: 10.1007/978-3-319-67669-2doiSubjects--Topical Terms:

568984
Computational intelligence.

LC Class. No.: Q342

Dewey Class. No.: 006.3

Nature-Inspired Algorithms and Applied Optimization
LDR:02825nam a22004095i 4500 001 997023
003 DE-He213
005 20200703154243.0
007 cr nn 008mamaa
008 201225s2018 gw | s |||| 0|eng d
020 $a 9783319676692 $9 978-3-319-67669-2
024 7 $a 10.1007/978-3-319-67669-2 $2 doi
035 $a 978-3-319-67669-2
050 4 $a Q342
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.3 $2 23
245 1 0 $a Nature-Inspired Algorithms and Applied Optimization $h [electronic resource] / $c edited by Xin-She Yang.
250 $a 1st ed. 2018.
264 1 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a XI, 330 p. 42 illus., 28 illus. in color. $b online resource.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
347 $a text file $b PDF $2 rda
490 1 $a Studies in Computational Intelligence, $x 1860-949X ; $v 744
505 0 $a Mathematical 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 $a This 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.
650 0 $a Computational intelligence. $3 568984
650 0 $a Artificial intelligence. $3 559380
650 0 $a Algorithms. $3 527865
650 0 $a Mathematical optimization. $3 527675
650 1 4 $a Computational Intelligence. $3 768837
650 2 4 $a Artificial Intelligence. $3 646849
650 2 4 $a Optimization. $3 669174
700 1 $a Yang, Xin-She. $4 edt $4 http://id.loc.gov/vocabulary/relators/edt $3 786470
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer Nature eBook
776 0 8 $i Printed edition: $z 9783319676685
776 0 8 $i Printed edition: $z 9783319676708
776 0 8 $i Printed edition: $z 9783319884653
830 0 $a Studies in Computational Intelligence, $x 1860-949X ; $v 564 $3 1253640
856 4 0 $u https://doi.org/10.1007/978-3-319-67669-2
912 $a ZDB-2-ENG
912 $a ZDB-2-SXE
950 $a Engineering (SpringerNature-11647)
950 $a Engineering (R0) (SpringerNature-43712)