LEADER 03550nam 22005775 450 001 9910590081903321 005 20251113190227.0 010 $a3-031-07512-9 024 7 $a10.1007/978-3-031-07512-4 035 $a(MiAaPQ)EBC7079610 035 $a(Au-PeEL)EBL7079610 035 $a(CKB)24767660900041 035 $a(PPN)264193547 035 $a(OCoLC)1344542848 035 $a(DE-He213)978-3-031-07512-4 035 $a(EXLCZ)9924767660900041 100 $a20220831d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHandbook of Nature-Inspired Optimization Algorithms: The State of the Art $eVolume I: Solving Single Objective Bound-Constrained Real-Parameter Numerical Optimization Problems /$fedited by Ali Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan 205 $a1st ed. 2022. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2022. 215 $a1 online resource (282 pages) 225 1 $aStudies in Systems, Decision and Control,$x2198-4190 ;$v212 311 08$aPrint version: Mohamed, Ali Handbook of Nature-Inspired Optimization Algorithms: the State of the Art Cham : Springer International Publishing AG,c2022 9783031075117 327 $aChaotic-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. 330 $aThe introduction of nature-inspired optimization algorithms (NIOAs), over the past three decades, helped solve nonlinear, high-dimensional, and complex computational optimization problems. NIOAs have been originally developed to overcome the challenges of global optimization problems such as nonlinearity, non-convexity, non-continuity, non-differentiability, and/or multimodality which traditional numerical optimization techniques had difficulties solving. The main objective for this book is to make available a self-contained collection of modern research addressing the general bound-constrained optimization problems in many real-world applications using nature-inspired optimization algorithms. This book is suitable for a graduate class on optimization, but will also be useful for interested senior students working on their research projects. 410 0$aStudies in Systems, Decision and Control,$x2198-4190 ;$v212 606 $aComputational intelligence 606 $aArtificial intelligence 606 $aComputational Intelligence 606 $aArtificial Intelligence 615 0$aComputational intelligence. 615 0$aArtificial intelligence. 615 14$aComputational Intelligence. 615 24$aArtificial Intelligence. 676 $a519.3 676 $a519.6 702 $aMohamed$b Ali 702 $aOliva$b Diego 702 $aNagaratnam$b Ponnuthurai 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910590081903321 996 $aHandbook of Nature-Inspired Optimization Algorithms: The State of the Art$94462643 997 $aUNINA