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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 levels of learn-by-doing activities through the book.
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.
Overview
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 ...