Linear Programming and Generalizations: A Problem-Based Introduction with Spreadsheets

ISBN-13: 9781489977717 / Angielski / Miękka / 2017 / 673 str.

Eric V. DeNardo

Opis

Written by a leading expert in Mathematical Programming methods, this book introduces students to the conceptual ideas of Linear Programming methodology and its generalizations. The book has a distinct application focus with emphasis on application problems.

Recenzje

From the reviews:

"This text includes a more in-depth review of LP, lending the student thorough knowledge of the art and science of problem solving using LP. ... Undergraduate students in applied commerce or business programs are clearly part of the audience. It is also suitable for a course that introduces LP, its application, and its integration with widely used software ... . Practitioners with an interest in refreshing their knowledge in LP or expanding their knowledge to include LP will be equally satisfied by this book." (Geoffrey T. Pond, Interfaces, Vol. 42 (3), May-June, 2012)

Spis treści

Chapter 1. Introduction to Linear Programs.- Chapter 2. Spreadsheet Computation.- Chapter 3. Mathematical Preliminaries.- Chapter 4. The Simplex Method, Part 1.- Chapter 5. Analyzing Linear Programs.- Chapter 6. The Simplex Method, Part 2.- Chapter 7. A Survey of Optimization Problems.- Chapter 8. Path-Length Problems and Dynamic Programming.- Chapter 9. Flows in Networks.- Chapter 10. Vector Spaces and Linear Programs.- Chapter 11. Multipliers and the Simplex Method.- Chapter 12. Duality.- Chapter 13. The Dual Simplex Pivot and Its Uses.- Chapter 14. Introduction to Game Theory.- Chapter 15. The Bi-Matrix Game.- Chapter 16. Fixed Points and Equilibria.- Chapter 17. Convex Sets.- Chapter 18. Differentiation.- Chapter 19. Convex Functions.- Chapter 20.- Nonlinear Programs.

Blurb

This book on constrained optimization is novel in that it fuses these themes: • use examples to introduce general ideas; • engage the student in spreadsheet computation; • survey the uses of constrained optimization;. • investigate game theory and nonlinear optimization, • link the subject to economic reasoning, and • present the requisite mathematics. Blending these themes makes constrained optimization more accessible and more valuable. It stimulates the student’s interest, quickens the learning process, reveals connections to several academic and professional fields, and deepens the student’s grasp of the relevant mathematics. The book is designed for use in courses that focus on the applications of constrained optimization, in courses that emphasize the theory, and in courses that link the subject to economics.