An Optimization Primer : On Models, Algorithms, and Duality

Lawrence Nazareth

ISBN 10: 0387211551 / ISBN 13: 9780387211558

Editore: Springer New York, Springer New York, 2004

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - Optimization is the task of finding the best member of a finite or infinite set of possible choices, based on some objective measure of the merit of each choice in the set.The three key facets of the subject are the art of constructing optimization models, the science of discovering and implementing efficient algorithms for solving optimization models, and the mathematics of optimization models and algorithms.Thisbook provides a very gentle introduction to modeling, algorithms and duality and should appeal to several audiences at once: students (as a supplement to a regular textbook), general readers such as people in business (as an introduction to how optimization affects their everyday lives), and instructors (as a source of ideas for how to teach optimization differently).

Codice articolo 9780387211558

Dati bibliografici

• Titolo: An Optimization Primer : On Models, Algorithms, and Duality
• Editore: Springer New York, Springer New York
• Data di pubblicazione: 2004
• Lingua: Inglese
• ISBN 10: 0387211551
• ISBN 13: 9780387211558
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 8 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 8 millimetri di profondità
• Peso: 201 grammi

Descrizione articolo

Riassunto

This book introduces a general audience to the main facets of optimization.

Very little mathematical background is assumed.

It should appeal to students, teachers, and a general audience interested in how optimization affects their everyday life, such as people in business. 

Dalla quarta di copertina

Optimization is the art, science and mathematics of finding the "best" member of a finite or infinite set of possible choices, based on some objective measure of the merit of each choice in the set. Three key facets of the subject are:

- the construction of optimization models that capture the range of available choices within a feasible set and the measure-of-merit of any particular choice in a feasible set relative to its competitors;

- the invention and implementation of efficient algorithms for solving optimization models;

- a mathematical principle of duality that relates optimization models to one another in a fundamental way. Duality cuts across the entire field of optimization and is useful, in particular, for identifying optimality conditions, i.e., criteria that a given member of a feasible set must satisfy in order to be an optimal solution.

This book provides a gentle introduction to the above topics and will be of interest to college students taking an introductory course in optimization, high school students beginning their studies in mathematics and science, the general reader looking for an overall sense of the field of optimization, and specialists in optimization interested in developing new ways of teaching the subject to their students.

John Lawrence Nazareth is Professor Emeritus in the Department of Mathematics at Washington State University and Affiliate Professor in the Department of Applied Mathematics at the University of Washington. He is the author of two recent books also published by Springer-Verlag which explore the above topics in more depth, Differentiable Optimization and Equation Solving (2003) and DLP and Extensions: An Optimization Model and Decision Support System (2001).