Mathematical Optimization Terminology

• Author : Andre A. Keller
• Publisher : Academic Press
• Release : 10 November 2017

Mathematical Optimization Terminology: A Comprehensive Glossary of Terms is a practical book with the essential formulations, illustrative examples, real-world applications and main references on the topic. This book helps readers gain a more practical understanding of optimization, enabling them to apply it to their algorithms. This book also addresses the need for a practical publication that introduces these concepts and techniques. Discusses real-world applications of optimization and how it can be used in algorithms Explains the essential formulations of optimization

• Author : Anonim
• Publisher : Unknown Publisher
• Release : 14 April 2021

• Author : Gerard Cornuejols,Reha Tütüncü
• Publisher : Cambridge University Press
• Release : 21 December 2006

Optimization models play an increasingly important role in financial decisions. This is the first textbook devoted to explaining how recent advances in optimization models, methods and software can be applied to solve problems in computational finance more efficiently and accurately. Chapters discussing the theory and efficient solution methods for all major classes of optimization problems alternate with chapters illustrating their use in modeling problems of mathematical finance. The reader is guided through topics such as volatility estimation, portfolio optimization problems

• Author : Stephen Boyd,Stephen P. Boyd,Lieven Vandenberghe
• Publisher : Cambridge University Press
• Release : 08 March 2004

Convex optimization problems arise frequently in many different fields. This book provides a comprehensive introduction to the subject, and shows in detail how such problems can be solved numerically with great efficiency. The book begins with the basic elements of convex sets and functions, and then describes various classes of convex optimization problems. Duality and approximation techniques are then covered, as are statistical estimation techniques. Various geometrical problems are then presented, and there is detailed discussion of unconstrained and constrained

• Author : Sergiy Butenko,Panos M. Pardalos
• Publisher : CRC Press
• Release : 11 March 2014

For students in industrial and systems engineering (ISE) and operations research (OR) to understand optimization at an advanced level, they must first grasp the analysis of algorithms, computational complexity, and other concepts and modern developments in numerical methods. Satisfying this prerequisite, Numerical Methods and Optimization: An Intro

• Author : Edwin K. P. Chong,Stanislaw H. Zak
• Publisher : John Wiley & Sons
• Release : 05 April 2004

A modern, up-to-date introduction to optimization theory andmethods This authoritative book serves as an introductory text tooptimization at the senior undergraduate and beginning graduatelevels. With consistently accessible and elementary treatment ofall topics, An Introduction to Optimization, Second Edition helpsstudents build a solid working knowledge of the field, includingunconstrained optimization, linear programming, and constrainedoptimization. Supplemented with more than one hundred tables and illustrations,an extensive bibliography, and numerous worked examples toillustrate both theory and algorithms, this book alsoprovides: * A review of

• Author : Anonim
• Publisher : Unknown Publisher
• Release : 14 April 1971

• Author : Michael H. Veatch
• Publisher : John Wiley & Sons
• Release : 13 January 2021

Discover the practical impacts of current methods of optimization with this approachable, one-stop resource Linear and Convex Optimization: A Mathematical Approach delivers a concise and unified treatment of optimization with a focus on developing insights in problem structure, modeling, and algorithms. Convex optimization problems are covered in detail because of their many applications and the fast algorithms that have been developed to solve them. Experienced researcher and undergraduate teacher Mike Veatch presents the main algorithms used in linear, integer, and

• Author : Ferruh Erdogdu
• Publisher : CRC Press
• Release : 09 December 2008

While mathematically sophisticated methods can be used to better understand and improve processes, the nonlinear nature of food processing models can make their dynamic optimization a daunting task. With contributions from a virtual who’s who in the food processing industry, Optimization in Food Engineering evaluates the potential uses and limitations of optimization techniques for food processing, including classical methods, artificial intelligence-genetic algorithms, multi-objective optimization procedures, and computational fluid dynamics. The book begins by delineating the fundamentals and methods for

• Author : Javier Del Ser Lorente,Eneko Osaba
• Publisher : BoD – Books on Demand
• Release : 18 July 2018

Nature-inspired algorithms have a great popularity in the current scientific community, being the focused scope of many research contributions in the literature year by year. The rationale behind the acquired momentum by this broad family of methods lies on their outstanding performance evinced in hundreds of research fields and problem instances. This book gravitates on the development of nature-inspired methods and their application to stochastic, dynamic and robust optimization. Topics covered by this book include the design and development of

• Author : J.-B. Hiriart-Urruty
• Publisher : Elsevier
• Release : 01 January 1986

Optimization, as examined here, ranges from differential equations to problems arising in Mechanics and Statistics. The main topics covered are: calculations of variations and nonlinear elasticity, optimal control, analysis and optimization in problems dealing with nondifferentiable data, duality techniques, algorithms in mathematical programming and optimal control.

• Author : Charles L. Byrne
• Publisher : CRC Press
• Release : 11 August 2014

Give Your Students the Proper Groundwork for Future Studies in Optimization A First Course in Optimization is designed for a one-semester course in optimization taken by advanced undergraduate and beginning graduate students in the mathematical sciences and engineering. It teaches students the basics of continuous optimization and helps them better understand the mathematics from previous courses. The book focuses on general problems and the underlying theory. It introduces all the necessary mathematical tools and results. The text covers the fundamental

• Author : North Atlantic Treaty Organization. Advisory Group for Aerospace Research and Development. Structures and Materials Panel
• Publisher : Unknown Publisher
• Release : 14 April 1971

The document describes the present state of development of the use of mathematical programming techniques in the optimum design of aerospace and similar structures. Although optimization with respect to cost is considered when possible, the main emphasis is on the minimization of weight, due to the overwhelming importance of this parameter in aerospace applications, and also due to the fact that it is one of the few merit functions that can be defined with reasonable precision. The use of mathematical

• Author : P. Adby
• Publisher : Springer Science & Business Media
• Release : 09 March 2013

During the last decade the techniques of non-linear optim ization have emerged as an important subject for study and research. The increasingly widespread application of optim ization has been stimulated by the availability of digital computers, and the necessity of using them in the investigation of large systems. This book is an introduction to non-linear methods of optimization and is suitable for undergraduate and post graduate courses in mathematics, the physical and social sciences, and engineering. The first half of

• Author : Niclas Andreasson,Anton Evgrafov,Michael Patriksson
• Publisher : Courier Dover Publications
• Release : 15 January 2020

This treatment focuses on the analysis and algebra underlying the workings of convexity and duality and necessary/sufficient local/global optimality conditions for unconstrained and constrained optimization problems. 2015 edition.