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Handbook of nature-inspired optimiza...

Mohamed, Ali Wagdy.

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Handbook of nature-inspired optimization algorithms = the state of the art.. Volume I,. Solving single objective bound-constrained real-parameter numerical optimization problems /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Handbook of nature-inspired optimization algorithms/ edited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan.
Reminder of title:	the state of the art.
remainder title:	Solving single objective bound-constrained real-parameter numerical optimization problems
other author:	Mohamed, Ali Wagdy.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	x, 279 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Chaotic-SCA Salp Swarm Algorithm Enhanced with Opposition Based Learning: Application to Decrease Carbon Footprint in Patient Flow -- Design and Performance Evaluation of Objective Functions Based on Various Measures of Fuzzy Entropies for Image Segmentation using Grey Wolf Optimization -- Improved Artificial Bee Colony Algorithm with Adaptive Pursuit Based Strategy Selection -- Beetle Antennae Search Algorithm for the Motion Planning of Industrial Manipulator -- Solving Optimal Power Flow with Considering Placement of TCSC and FACTS Cost Using Cuckoo Search Algorithm.
Contained By:	Springer Nature eBook
Subject:	Mathematical optimization. -
Online resource:	https://doi.org/10.1007/978-3-031-07512-4
ISBN:	9783031075124

Handbook of nature-inspired optimization algorithms = the state of the art.. Volume I,. Solving single objective bound-constrained real-parameter numerical optimization problems /
Handbook of nature-inspired optimization algorithmsthe state of the art.Volume I,Solving single objective bound-constrained real-parameter numerical optimization problems /[electronic resource] :Solving single objective bound-constrained real-parameter numerical optimization problemsedited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan. - Cham :Springer International Publishing :2022. - x, 279 p. :ill. (some col.), digital ;24 cm. - Studies in systems, decision and control,v. 2122198-4190 ;. - Studies in systems, decision and control ;v. 212..

Chaotic-SCA Salp Swarm Algorithm Enhanced with Opposition Based Learning: Application to Decrease Carbon Footprint in Patient Flow -- Design and Performance Evaluation of Objective Functions Based on Various Measures of Fuzzy Entropies for Image Segmentation using Grey Wolf Optimization -- Improved Artificial Bee Colony Algorithm with Adaptive Pursuit Based Strategy Selection -- Beetle Antennae Search Algorithm for the Motion Planning of Industrial Manipulator -- Solving Optimal Power Flow with Considering Placement of TCSC and FACTS Cost Using Cuckoo Search Algorithm.

The introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving. The main objective for this book is to make available a self-contained collection of modern research addressing the general bound-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: 9783031075124

Standard No.: 10.1007/978-3-031-07512-4doiSubjects--Topical Terms:

517763
Mathematical optimization.

LC Class. No.: QA402.5

Dewey Class. No.: 519.6

Handbook of nature-inspired optimization algorithms = the state of the art.. Volume I,. Solving single objective bound-constrained real-parameter numerical optimization problems /
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505 0 $a Chaotic-SCA Salp Swarm Algorithm Enhanced with Opposition Based Learning: Application to Decrease Carbon Footprint in Patient Flow -- Design and Performance Evaluation of Objective Functions Based on Various Measures of Fuzzy Entropies for Image Segmentation using Grey Wolf Optimization -- Improved Artificial Bee Colony Algorithm with Adaptive Pursuit Based Strategy Selection -- Beetle Antennae Search Algorithm for the Motion Planning of Industrial Manipulator -- Solving Optimal Power Flow with Considering Placement of TCSC and FACTS Cost Using Cuckoo Search Algorithm.
520 $a The introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving. The main objective for this book is to make available a self-contained collection of modern research addressing the general bound-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.
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