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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 /
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Handbook of Nature-Inspired Optimization Algorithms: The State of the Art/ edited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan.
其他題名:
Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems /
其他作者:
Suganthan, Ponnuthurai Nagaratnam.
面頁冊數:
X, 279 p. 94 illus., 73 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Artificial Intelligence. -
電子資源:
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 Algorithms: The State of the Art
Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems /[electronic resource] :edited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan. - 1st ed. 2022. - X, 279 p. 94 illus., 73 illus. in color.online resource. - Studies in Systems, Decision and Control,2122198-4190 ;. - Studies in Systems, Decision and Control,27.
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:
646849
Artificial Intelligence.
LC Class. No.: Q342
Dewey Class. No.: 006.3
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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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.
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