ABSTRACT

Linear Optimization and Dualiyy: A Modern Exposition departs from convention in significant ways. Standard linear programming textbooks present the material in the order in which it was discovered. Duality is treated as a difficult add-on after coverage of formulation, the simplex method, and polyhedral theory. Students end up without knowing duality in their bones.

This text brings in duality in Chapter 1 and carries duality all the way through the exposition. Chapter 1 gives a general definition of duality that shows the dual aspects of a matrix as a column of rows and a row of columns. The proof of weak duality in Chapter 2 is shown via the Lagrangian, which relies on matrix duality. The first three LP formulation examples in Chapter 3 are classic primal-dual pairs including the diet problem and 2-person zero sum games.

For many engineering students, optimization is their first immersion in rigorous mathematics. Conventional texts assume a level of mathematical sophistication they don’t have. This text embeds dozens of reading tips and hundreds of answered questions to guide such students.

Features

  • Emphasis on duality throughout
  • Practical tips for modeling and computation
  • Coverage of computational complexity and data structures
  • Exercises and problems based on the learning theory concept of the zone of proximal

development

  • Guidance for the mathematically unsophisticated reader

About the Author

Craig A. Tovey is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology. Dr. Tovey received an AB from Harvard College, an MS in computer science and a PhD in operations research from Stanford University. His principal activities are in operations research and its interdisciplinary applications. He received a Presidential Young Investigator Award and the Jacob Wolfowitz Prize for research in heuristics. He was named an Institute Fellow at Georgia Tech, and was recognized by the ACM Special Interest Group on Electronic Commerce with the Test of Time Award. Dr. Tovey received the 2016 Golden Goose Award for his research on bee foraging behavior leading to the development of the Honey Bee Algorithm.

chapter Chapter 1|32 pages

A Gentle Introduction to Optimization and Duality

chapter Chapter 2|28 pages

Introduction to Linear Programming

chapter Chapter 3|50 pages

Formulating and Solving Linear Programs

chapter Chapter 4|36 pages

Polyhedra

chapter Chapter 5|28 pages

The Simplex Method

chapter Chapter 6|36 pages

Variants of the Simplex Method

chapter Chapter 8|30 pages

Advanced Topics on Polyhedra

chapter Chapter 9|26 pages

Polynomial Time Algorithms

chapter Chapter 11|34 pages

Network Models and the Network Simplex Algorithm

chapter Chapter 12|26 pages

Shortest Path Models and Algorithms

chapter Chapter 13|22 pages

Specialized Algorithms for Maximum Flow and Minimum Cut

chapter Chapter 14|48 pages

Computational Complexity

chapter Chapter 15|28 pages

Formulating and Solving Integer Programs

chapter Chapter 16|18 pages

Elementary Nonlinear Programming Theory

chapter Chapter 17|14 pages

Introduction to Nonlinear Programming Algorithms

chapter Chapter 19|12 pages

Appendices