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Nature-inspired algorithms and appli...

Yang, Xin-She.

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Nature-inspired algorithms and applied optimization

Record Type:	Electronic resources : Monograph/item
Title/Author:	Nature-inspired algorithms and applied optimization/ edited by Xin-She Yang.
other author:	Yang, Xin-She.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	xi, 330 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	Natural computation. -
Online resource:	http://dx.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. - Cham :Springer International Publishing :2018. - xi, 330 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v.7441860-949X ;. - Studies in computational intelligence ;v.744..

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:

1002233
Natural computation.

LC Class. No.: QA76.9.N37

Dewey Class. No.: 006.38

Nature-inspired algorithms and applied optimization
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245 0 0 $a Nature-inspired algorithms and applied optimization $h [electronic resource] / $c edited by Xin-She Yang.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xi, 330 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-949X ; $v 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.
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650 2 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Algorithms. $3 536374
650 2 4 $a Optimization. $3 891104
700 1 $a Yang, Xin-She. $3 906652
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Studies in computational intelligence ; $v v.744. $3 3297515
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-67669-2
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