This textbook provides undergraduate students with an introduction to optimization and its uses for relevant and realistic problems. The only prerequisite for readers is a basic understanding of multivariable calculus because additional material, such as explanations of matrix tools, are provided in a series of Asides both throughout the text at relevant points and in a handy appendix.
The Basics of Practical Optimization presents step-by-step solutions for five prototypical examples that fit the general optimization model, along with instruction on using numerical methods to solve models and making informed use of the results. It also includes information on how to optimize while adjusting the method to accommodate various practical concerns; three fundamentally different approaches to optimizing functions under constraints; and ways to handle the special case when the variables are integers.
The author provides four types of learn-by-doing activities through the book: Exercises meant to be attempted as they are encountered and that are short enough for in-class use; Problems for lengthier in-class work or homework; Computational Problems for homework or a computer lab session; and Implementations usable as collaborative activities in the computer lab over extended periods of time.
The accompanying Web site offers the Mathematica notebooks that support the Implementations.
The Basics of Practical Optimization presents:
- Step-by-step solutions for five prototypical examples that fit the general optimization model.
- Instruction on using numerical methods to solve models and making informed use of the results.
- Information on how to optimize while adjusting the method to accommodate various practical concerns.
- Three fundamentally different approaches to optimizing functions under constraints.
- Ways to handle the special case when the variables are integers.
>The author provides four types of learn-by-doing activities through the book:
- Exercises meant to be attempted as they are encountered and that are short enough for in-class use.
- Problems for lengthier in-class work or homework.
- Computational Problems for homework or a computer lab session.
- Implementations usable as collaborative activities in the computer lab over extended periods of time.
>The accompanying Web site offers the Mathematica notebooks that support the Implementations.
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Produkt-Hinweis
Broschur/Paperback
Klebebindung
Maße
Höhe: 251 mm
Breite: 175 mm
Dicke: 10 mm
Gewicht
ISBN-13
978-0-89871-679-5 (9780898716795)
Schweitzer Klassifikation
Adam Levy is Professor and Chair of the Department of Mathematics at Bowdoin College. He was recognized in 1997 with the college's Sydney B. Korofsky prize for excellence in undergraduate teaching and has published over two dozen journal articles on optimization.
List of figures; List of tables; Preface; 1. Modeling; 2. Impractical optimization; 3. Basic practical optimization; 4. Some practical modifications; 5. How methods are ranked; 6. Constraints; 7. More practical modifications; 8. Integer variables; 9. Other methods; Appendix of asides; Bibliography; Index.
