This book is specifically designed to change the way deterministic optimization is taught to introductory students.
Toward this end, it exposes students to the broad scope of the topic, reinforces the basic principles, sparks
students' enthusiasm about the field, provides tools of immediate relevance and develops the skills necessary to
use those tools.
Table of Contents
1. Problem Solving with Mathematical Models.
2. Deterministic Optimization Models in Operations Research.
3. Improving Search.
4. Linear Programming Models.
5. Simplex Search for Linear Programming.
6. Interior Point Methods for Linear Programming.
7. Duality and Sensitivity in Linear Programming.
8. Multiobjective Optimization and Goal Programming.
9. Shortest Path and Discrete Dynamic Programming.
