03550nam 22005775 450 991059008190332120251113190227.03-031-07512-910.1007/978-3-031-07512-4(MiAaPQ)EBC7079610(Au-PeEL)EBL7079610(CKB)24767660900041(PPN)264193547(OCoLC)1344542848(DE-He213)978-3-031-07512-4(EXLCZ)992476766090004120220831d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierHandbook of Nature-Inspired Optimization Algorithms: The State of the Art Volume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems /edited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan1st ed. 2022.Cham :Springer International Publishing :Imprint: Springer,2022.1 online resource (282 pages)Studies in Systems, Decision and Control,2198-4190 ;212Print version: Mohamed, Ali Handbook of Nature-Inspired Optimization Algorithms: the State of the Art Cham : Springer International Publishing AG,c2022 9783031075117 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.Studies in Systems, Decision and Control,2198-4190 ;212Computational intelligenceArtificial intelligenceComputational IntelligenceArtificial IntelligenceComputational intelligence.Artificial intelligence.Computational Intelligence.Artificial Intelligence.519.3519.6Mohamed AliOliva DiegoNagaratnam PonnuthuraiMiAaPQMiAaPQMiAaPQBOOK9910590081903321Handbook of Nature-Inspired Optimization Algorithms: The State of the Art4462643UNINA