國立高雄大學圖資館 |

Chaotic meta-heuristic algorithms for optimal design of structures

Record Type:	Electronic resources : Monograph/item
Title/Author:	Chaotic meta-heuristic algorithms for optimal design of structuresby Ali Kaveh, Hossein Yousefpoor.
Author:	Kaveh, Ali.
other author:	Yousefpoor, Hossein.
Published:	Cham :Springer Nature Switzerland :2024.
Description:	xii, 342 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Metaheuristics.
Online resource:	https://doi.org/10.1007/978-3-031-48918-1
ISBN:	9783031489181$q(electronic bk.)

Chaotic meta-heuristic algorithms for optimal design of structures
Kaveh, Ali.

Chaotic meta-heuristic algorithms for optimal design of structures[electronic resource] /by Ali Kaveh, Hossein Yousefpoor. - Cham :Springer Nature Switzerland :2024. - xii, 342 p. :ill. (some col.), digital ;24 cm. - Studies in computational intelligence,v. 11291860-9503 ;. - Studies in computational intelligence ;v. 216..

Introduction -- Chaotic Maps and Meta-Heuristic Algorithms -- Chaotic Cyclical Parthenogenesis Algorithm -- Chaotic Teaching Learning-Based Optimization -- Chaotic Biogeography Based Optimization -- Chaotic Differential Evolution -- Chaotic Water Evaporation Optimization -- Chaotic Artificial Bees Colony -- Chaotic Imperialist Competitive Algorithm.

In this book, various chaos maps are embedded in eleven efficient and well-known metaheuristics and a significant improvement in the optimization results is achieved. The two basic steps of metaheuristic algorithms consist of exploration and exploitation. The imbalance between these stages causes serious problems for metaheuristic algorithms, which are immature convergence and stopping in local optima. Chaos maps with chaotic jumps can save algorithms from being trapped in local optima and lead to convergence toward global optima. Embedding these maps in the exploration phase, exploitation phase, or both simultaneously corresponds to three efficient and useful scenarios. By creating competition between different modes and increasing diversity in the search space and creating sudden jumps in the search phase, improvements are achieved for chaotic algorithms. Four Chaotic Algorithms, including Chaotic Cyclical Parthenogenesis Algorithm, Chaotic Water Evaporation Optimization, Chaotic Tug-of-War Optimization, and Chaotic Thermal Exchange Optimization are developed.

ISBN: 9783031489181$q(electronic bk.)

Standard No.: 10.1007/978-3-031-48918-1doiSubjects--Topical Terms:

757062
Metaheuristics.

LC Class. No.: QA76.9.A43

Dewey Class. No.: 005.13

Chaotic meta-heuristic algorithms for optimal design of structures
LDR:02533nmm a2200337 a 4500 001 663247
003 DE-He213
005 20240129082237.0
006 m d
007 cr nn 008maaau
008 241203s2024 sz s 0 eng d
020 $a 9783031489181$q(electronic bk.)
020 $a 9783031489174$q(paper)
024 7 $a 10.1007/978-3-031-48918-1 $2 doi
035 $a 978-3-031-48918-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.A43
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 005.13 $2 23
090 $a QA76.9.A43 $b K21 2024
100 1 $a Kaveh, Ali. $3 809590
245 1 0 $a Chaotic meta-heuristic algorithms for optimal design of structures $h [electronic resource] / $c by Ali Kaveh, Hossein Yousefpoor.
260 $a Cham : $b Springer Nature Switzerland : $b Imprint: Springer, $c 2024.
300 $a xii, 342 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in computational intelligence, $x 1860-9503 ; $v v. 1129
505 0 $a Introduction -- Chaotic Maps and Meta-Heuristic Algorithms -- Chaotic Cyclical Parthenogenesis Algorithm -- Chaotic Teaching Learning-Based Optimization -- Chaotic Biogeography Based Optimization -- Chaotic Differential Evolution -- Chaotic Water Evaporation Optimization -- Chaotic Artificial Bees Colony -- Chaotic Imperialist Competitive Algorithm.
520 $a In this book, various chaos maps are embedded in eleven efficient and well-known metaheuristics and a significant improvement in the optimization results is achieved. The two basic steps of metaheuristic algorithms consist of exploration and exploitation. The imbalance between these stages causes serious problems for metaheuristic algorithms, which are immature convergence and stopping in local optima. Chaos maps with chaotic jumps can save algorithms from being trapped in local optima and lead to convergence toward global optima. Embedding these maps in the exploration phase, exploitation phase, or both simultaneously corresponds to three efficient and useful scenarios. By creating competition between different modes and increasing diversity in the search space and creating sudden jumps in the search phase, improvements are achieved for chaotic algorithms. Four Chaotic Algorithms, including Chaotic Cyclical Parthenogenesis Algorithm, Chaotic Water Evaporation Optimization, Chaotic Tug-of-War Optimization, and Chaotic Thermal Exchange Optimization are developed.
650 0 $a Metaheuristics. $3 757062
650 0 $a Mathematical optimization. $3 183292
650 0 $a Chaotic behavior in systems. $3 182904
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Optimization. $3 274084
700 1 $a Yousefpoor, Hossein. $3 975492
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
830 0 $a Studies in computational intelligence ; $v v. 216. $3 380871
856 4 0 $u https://doi.org/10.1007/978-3-031-48918-1
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)