Evolutionary Algorithms for Power Optimization Problem

Joydeep Dutta

ISBN 10: 613896764X / ISBN 13: 9786138967644

Published by Scholars' Press, 2022

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - In Control System Engineering concerned here is Computational Intelligence (CI). Evolutionary algorithms (EA) fall under the domain of Computational Intelligence and it is dominating other categories of optimization techniques and gaining more research interest. Optimization techniques, having reached a degree of maturity in recent years, are being used in a wide spectrum of industries, including aerospace, automotive, chemical, electrical, construction, and manufacturing industries. With rapidly advancing computer technology, computers are becoming more powerful, and correspondingly, the size and the complexity of the problems that can be solved using optimization techniques are also increasing. To find out the parameter(s) value for making systems more efficient, fast, and reliable the need for robust, flexible, and improved optimization algorithms is increasing day by day. In this book, we have concentrated on optimizing real-world numerical optimization problems. Detailed analyses of some selected real-world optimization problems have been done.

Seller Inventory # 9786138967644

Bibliographic Details

• Title: Evolutionary Algorithms for Power Optimization Problem
• Publisher: Scholars' Press
• Publication Date: 2022
• Language: English
• ISBN 10: 613896764X
• ISBN 13: 9786138967644
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 7D millimeters 220 millimeters width by 150 millimeters height by 7 millimeters depth
• Weight: 179 grams

About this title

Synopsis

In Control System Engineering concerned here is Computational Intelligence (CI). Evolutionary algorithms (EA) fall under the domain of Computational Intelligence and it is dominating other categories of optimization techniques and gaining more research interest. Optimization techniques, having reached a degree of maturity in recent years, are being used in a wide spectrum of industries, including aerospace, automotive, chemical, electrical, construction, and manufacturing industries. With rapidly advancing computer technology, computers are becoming more powerful, and correspondingly, the size and the complexity of the problems that can be solved using optimization techniques are also increasing. To find out the parameter(s) value for making systems more efficient, fast, and reliable the need for robust, flexible, and improved optimization algorithms is increasing day by day. In this book, we have concentrated on optimizing real-world numerical optimization problems. Detailed analyses of some selected real-world optimization problems have been done.