東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Handbook of nature-inspired optimiza...

Mohamed, Ali Wagdy.

Linked to FindBook

Google Book

Amazon

博客來

Handbook of nature-inspired optimization algorithms = the state of the art.. Volume II,. Solving contrained single objective real-parameter optimization problems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Handbook of nature-inspired optimization algorithms/ edited by Ali Wagdy Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan.
Reminder of title:	the state of the art.
remainder title:	Solving contrained single objective real-parameter optimization problems
other author:	Mohamed, Ali Wagdy.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	x, 214 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Particle swarm optimization based optimization for in-dustry inspection -- Ant Algorithms: from Drawback Identification to Quality and Speed Improvement -- Fault location techniques based on traveling waves with application in the protection of distribution systems with renewable energy and particle swarm optimization -- Improved Particle Swarm Optimization and Non-Quadratic Penalty Method for Non-Linear Programming Problems with Equality Constraints -- Recent Trends in Face Recognition Using Metaheuristic Optimization.
Contained By:	Springer Nature eBook
Subject:	Mathematical optimization. -
Online resource:	https://doi.org/10.1007/978-3-031-07516-2
ISBN:	9783031075162

Handbook of nature-inspired optimization algorithms = the state of the art.. Volume II,. Solving contrained single objective real-parameter optimization problems /
Handbook of nature-inspired optimization algorithmsthe state of the art.Volume II,Solving contrained single objective real-parameter optimization problems /[electronic resource] :Solving contrained single objective real-parameter optimization problemsedited by Ali Wagdy Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan. - Cham :Springer International Publishing :2022. - x, 214 p. :ill. (some col.), digital ;24 cm. - Studies in systems, decision and control,v. 2132198-4190 ;. - Studies in systems, decision and control ;v. 213..

Particle swarm optimization based optimization for in-dustry inspection -- Ant Algorithms: from Drawback Identification to Quality and Speed Improvement -- Fault location techniques based on traveling waves with application in the protection of distribution systems with renewable energy and particle swarm optimization -- Improved Particle Swarm Optimization and Non-Quadratic Penalty Method for Non-Linear Programming Problems with Equality Constraints -- Recent Trends in Face Recognition Using Metaheuristic Optimization.

This book presents recent contributions and significant development, advanced issues, and challenges. In real-world problems and applications, most of the optimization problems involve different types of constraints. These problems are called constrained optimization problems (COPs) The optimization of the constrained optimization problems is considered a challenging task since the optimum solution(s) must be feasible. In their original design, evolutionary algorithms (EAs) are able to solve unconstrained optimization problems effectively. As a result, in the past decade, many researchers have developed a variety of constraint handling techniques, incorporated into (EAs) designs, to counter this deficiency. The main objective for this book is to make available a self-contained collection of modern research addressing the general constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.

ISBN: 9783031075162

Standard No.: 10.1007/978-3-031-07516-2doiSubjects--Topical Terms:

517763
Mathematical optimization.

LC Class. No.: QA402.5 / .H35 2022

Dewey Class. No.: 519.6

Handbook of nature-inspired optimization algorithms = the state of the art.. Volume II,. Solving contrained single objective real-parameter optimization problems /
LDR:02934nmm a2200337 a 4500 001 2303357
003 DE-He213
005 20220903150638.0
007 cr nn 008maaau
008 230409s2022 sz s 0 eng d
020 $a 9783031075162 $q (electronic bk.)
020 $a 9783031075155 $q (paper)
024 7 $a 10.1007/978-3-031-07516-2 $2 doi
035 $a 978-3-031-07516-2
040 $a GP $c GP
041 0 $a eng
050 4 $a QA402.5 $b .H35 2022
072 7 $a UYQ $2 bicssc
072 7 $a TEC009000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 519.6 $2 23
090 $a QA402.5 $b .H236 2022
245 0 0 $a Handbook of nature-inspired optimization algorithms $h [electronic resource] : $b the state of the art. $n Volume II, $p Solving contrained single objective real-parameter optimization problems / $c edited by Ali Wagdy Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan.
246 3 0 $a Solving contrained single objective real-parameter optimization problems
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a x, 214 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Studies in systems, decision and control, $x 2198-4190 ; $v v. 213
505 0 $a Particle swarm optimization based optimization for in-dustry inspection -- Ant Algorithms: from Drawback Identification to Quality and Speed Improvement -- Fault location techniques based on traveling waves with application in the protection of distribution systems with renewable energy and particle swarm optimization -- Improved Particle Swarm Optimization and Non-Quadratic Penalty Method for Non-Linear Programming Problems with Equality Constraints -- Recent Trends in Face Recognition Using Metaheuristic Optimization.
520 $a This book presents recent contributions and significant development, advanced issues, and challenges. In real-world problems and applications, most of the optimization problems involve different types of constraints. These problems are called constrained optimization problems (COPs) The optimization of the constrained optimization problems is considered a challenging task since the optimum solution(s) must be feasible. In their original design, evolutionary algorithms (EAs) are able to solve unconstrained optimization problems effectively. As a result, in the past decade, many researchers have developed a variety of constraint handling techniques, incorporated into (EAs) designs, to counter this deficiency. The main objective for this book is to make available a self-contained collection of modern research addressing the general constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects.
650 0 $a Mathematical optimization. $3 517763
650 0 $a Nature-inspired algorithms. $3 3451303
650 1 4 $a Computational Intelligence. $3 1001631
650 2 4 $a Artificial Intelligence. $3 769149
700 1 $a Mohamed, Ali Wagdy. $3 3594351
700 1 $a Oliva, Diego. $3 3218447
700 1 $a Suganthan, Ponnuthurai Nagaratnam. $3 2157647
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Studies in systems, decision and control ; $v v. 213. $3 3604534
856 4 0 $u https://doi.org/10.1007/978-3-031-07516-2
950 $a Intelligent Technologies and Robotics (SpringerNature-42732)