ID - 131905120 TI - Handbook of Nature-Inspired Optimization Algorithms: The State of the Art : Volume II: Solving Constrained Single Objective Real-Parameter Optimization Problems AU - Mohamed, Ali Wagdy AU - Oliva, Diego AU - Suganthan, Ponnuthurai Nagaratnam PY - 2022 SN - 9783031075162 9783031075155 9783031075179 9783031075186 PB - Cham Springer International Publishing DB - UniCat KW - Artificial intelligence. Robotics. Simulation. Graphics KW - neuronale netwerken KW - fuzzy logic KW - cybernetica KW - KI (kunstmatige intelligentie) KW - AI (artificiële intelligentie) UR - https://www.unicat.be/uniCat?func=search&query=sysid:131905120 AB - 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. ER -