Basics Practical Optimization by Levy Adam (20 results)

Condition: New. pp. 400.

Soft cover. Condition: New. 1st Edition. Contents: 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. Appendices. Bibliography. Index. 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 materials, 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 book 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, and ways to handle the special case when the variables are integers. The author provides four types of learn-by-doing activities throughout 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 This textbook is appropriate for undergraduate students who have taken a multivariable calculus course. Keywords: optimization; linear programming; applied mathematics; modelling; numerical methods.

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Paperback. Condition: New. Second Edition. Optimization is presented in most multivariable calculus courses as an application of the gradient, and while this treatment makes sense for a calculus course, there is much more to the theory of optimization. Optimization problems are generated constantly, and the theory of optimization has grown and developed in response to the challenges presented by these problems. This textbook aims to show readers how optimization is done in practice and help them to develop an appreciation for the richness of the theory behind the practice.Exercises, problems (including modeling and computational problems), and implementations are incorporated throughout the text to help students learn by doing. Python notes are inserted strategically to help readers complete computational problems and implementations.The Basics of Practical Optimization, Second Edition is intended for undergraduates who have completed multivariable calculus, as well as anyone interested in optimization. The book is appropriate for a course that complements or replaces a standard linear programming course.

Paperback. Condition: new. Paperback. Optimization is presented in most multivariable calculus courses as an application of the gradient, and while this treatment makes sense for a calculus course, there is much more to the theory of optimization. Optimization problems are generated constantly, and the theory of optimization has grown and developed in response to the challenges presented by these problems. This textbook aims to show readers how optimization is done in practice and help them to develop an appreciation for the richness of the theory behind the practice.Exercises, problems (including modeling and computational problems), and implementations are incorporated throughout the text to help students learn by doing. Python notes are inserted strategically to help readers complete computational problems and implementations.The Basics of Practical Optimization, Second Edition is intended for undergraduates who have completed multivariable calculus, as well as anyone interested in optimization. The book is appropriate for a course that complements or replaces a standard linear programming course. Shows readers how optimization is done in practice and helps them to develop an appreciation for the richness of the theory behind the practice. Exercises, problems (including modeling and computational problems), and implementations are incorporated throughout the text to help students learn by doing. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New. 2023. 2nd Edition. paperback. . . . . .

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Condition: New. 2023. 2nd Edition. paperback. . . . . . Books ship from the US and Ireland.

Paperback. Condition: Brand New. 2nd edition. 160 pages. 10.02x6.88x0.46 inches. In Stock.

Condition: new.

Paperback. Condition: New. Second Edition. Optimization is presented in most multivariable calculus courses as an application of the gradient, and while this treatment makes sense for a calculus course, there is much more to the theory of optimization. Optimization problems are generated constantly, and the theory of optimization has grown and developed in response to the challenges presented by these problems. This textbook aims to show readers how optimization is done in practice and help them to develop an appreciation for the richness of the theory behind the practice.Exercises, problems (including modeling and computational problems), and implementations are incorporated throughout the text to help students learn by doing. Python notes are inserted strategically to help readers complete computational problems and implementations.The Basics of Practical Optimization, Second Edition is intended for undergraduates who have completed multivariable calculus, as well as anyone interested in optimization. The book is appropriate for a course that complements or replaces a standard linear programming course.

Paperback. Condition: new. Paperback. Optimization is presented in most multivariable calculus courses as an application of the gradient, and while this treatment makes sense for a calculus course, there is much more to the theory of optimization. Optimization problems are generated constantly, and the theory of optimization has grown and developed in response to the challenges presented by these problems. This textbook aims to show readers how optimization is done in practice and help them to develop an appreciation for the richness of the theory behind the practice.Exercises, problems (including modeling and computational problems), and implementations are incorporated throughout the text to help students learn by doing. Python notes are inserted strategically to help readers complete computational problems and implementations.The Basics of Practical Optimization, Second Edition is intended for undergraduates who have completed multivariable calculus, as well as anyone interested in optimization. The book is appropriate for a course that complements or replaces a standard linear programming course. Shows readers how optimization is done in practice and helps them to develop an appreciation for the richness of the theory behind the practice. Exercises, problems (including modeling and computational problems), and implementations are incorporated throughout the text to help students learn by doing. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.