03825nam 22005895 450 991059103810332120251113191826.03-031-07516-110.1007/978-3-031-07516-2(MiAaPQ)EBC7080270(Au-PeEL)EBL7080270(CKB)24779133800041(PPN)264956699(OCoLC)1344159780(DE-He213)978-3-031-07516-2(EXLCZ)992477913380004120220903d2022 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierHandbook of Nature-Inspired Optimization Algorithms: The State of the Art Volume II: Solving Constrained Single Objective Real-Parameter Optimization Problems /edited by Ali Wagdy Mohamed, Diego Oliva, Ponnuthurai Nagaratnam Suganthan1st ed. 2022.Cham :Springer International Publishing :Imprint: Springer,2022.1 online resource (220 pages)Studies in Systems, Decision and Control,2198-4190 ;213Print version: Mohamed, Ali Wagdy Handbook of Nature-Inspired Optimization Algorithms: the State of the Art Cham : Springer International Publishing AG,c2022 9783031075155 Includes bibliographical references.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.Studies in Systems, Decision and Control,2198-4190 ;213Computational intelligenceArtificial intelligenceComputational IntelligenceArtificial IntelligenceComputational intelligence.Artificial intelligence.Computational Intelligence.Artificial Intelligence.519.3519.6Mohamed Ali Wagdy1978-Oliva DiegoSuganthan Ponnuthurai NagaratnamMiAaPQMiAaPQMiAaPQBOOK9910591038103321Handbook of Nature-Inspired Optimization Algorithms: The State of the Art4462643UNINA