Handbook of Nature-Inspired Optimization Algorithms: The State of the Art: Volume II: Solving Constrained Single Objective Real-Parameter Optimization Problems

This book presents recent contributions and significant development in constrained optimization problems, with a focus on nature-inspired optimization algorithms. It is suitable for graduate students and researchers working on optimization.

Format: Hardback
Length: 214 pages
Publication date: 04 September 2022
Publisher: Springer International Publishing AG

This book presents the latest advancements, cutting-edge issues, and formidable challenges in the field of optimization. In the realm of real-world problems and applications, a significant majority of optimization problems entail diverse types of constraints. These complex problems are referred to as constrained optimization problems (COPs). The task of optimizing constrained optimization problems poses significant difficulties, as the optimal solutions must be both feasible and viable. While evolutionary algorithms (EAs) were initially designed to effectively solve unconstrained optimization problems, it became evident that they lacked the capability to handle constraints effectively. Consequently, over the past decade, a multitude of researchers has dedicated their efforts to developing diverse constraint handling techniques, which have been seamlessly integrated into EA designs.

The primary goal of this book is to provide a comprehensive and self-contained resource that encompasses modern research on addressing general constrained optimization problems in a wide range of real-world applications through the utilization of nature-inspired optimization algorithms. This book is designed to serve as a valuable textbook for graduate-level courses in optimization, as well as a valuable reference for senior students engaged in research projects.

Weight: 506g
Dimension: 235 x 155 (mm)
ISBN-13: 9783031075155
Edition number: 1st ed. 2022