Rounded Branch and Bound Method for Mixed Integer Nonlinear Programming

Jacob Akoka

ISBN 10: 1332280684 / ISBN 13: 9781332280681

Published by Forgotten Books, 2018

About this Item

Print on Demand. This book presents an innovative method for addressing mixed-integer nonlinear programming, a prevalent type of mathematical optimization problem frequently encountered in various fields, such as engineering, economics, and finance. The technique, known as the Bounded Branch and Bound method, is thoroughly described, encompassing its theoretical foundations, practical implementation, and diverse applications. The author delves into both convex and non-convex formulations, offering comprehensive guidance on solving such complex problems. At its core, this book contributes to the broader realm of applied mathematics, particularly optimization theory. By extending existing knowledge on nonlinear programming, it provides a valuable tool for researchers grappling with intricate real-world scenarios. The author's in-depth analysis of the proposed method, coupled with its wide range of applications, makes this book an indispensable reference for academics, professionals, and students seeking advanced insights into this crucial area of research. This book is a reproduction of an important historical work, digitally reconstructed using state-of-the-art technology to preserve the original format. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in the book.

Seller Inventory # 9781332280681_0

Bibliographic Details

• Title: Rounded Branch and Bound Method for Mixed Integer Nonlinear Programming
• Publisher: Forgotten Books
• Publication Date: 2018
• Language: English
• ISBN 10: 1332280684
• ISBN 13: 9781332280681
• Binding: Paperback
• Condition: New
• Book Type: print-on-demand item
• Seller catalogs:
  • Calculus

About this title

Synopsis

This book presents an innovative method for addressing mixed-integer nonlinear programming, a prevalent type of mathematical optimization problem frequently encountered in various fields, such as engineering, economics, and finance. The technique, known as the Bounded Branch and Bound method, is thoroughly described, encompassing its theoretical foundations, practical implementation, and diverse applications. The author delves into both convex and non-convex formulations, offering comprehensive guidance on solving such complex problems. At its core, this book contributes to the broader realm of applied mathematics, particularly optimization theory. By extending existing knowledge on nonlinear programming, it provides a valuable tool for researchers grappling with intricate real-world scenarios. The author's in-depth analysis of the proposed method, coupled with its wide range of applications, makes this book an indispensable reference for academics, professionals, and students seeking advanced insights into this crucial area of research.