Handbook of Nature-Inspired Optimization Algorithms: The State of the Art - Volume II: Solving Constrained Single Objective Real-Parameter Optimization Problems (Hardcover, 1st ed. 2022)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Systems, Decision and Control, 213
Release date:	September 2022
First published:	2022
Editors:	Ali Wagdy Mohamed • Diego Oliva • Ponnuthurai Nagaratnam Suganthan
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	214
Edition:	1st ed. 2022
ISBN-13:	978-3-03-107515-5
Categories:	Books > Computing & IT > Applications of computing > Artificial intelligence > General Promotions
LSN:	3-03-107515-3
Barcode:	9783031075155

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