Julia Programming for Operations Research

Last Updated: December 2020





Based on Julia v1.3+ and JuMP v0.21+





The main motivation of writing this book was to help the author himself. He is a professor in the field of operations research, and his daily activities involve building models of mathematical optimization, developing algorithms for solving the problems, implementing those algorithms using computer programming languages, experimenting with data, etc. Three languages are involved: human language, mathematical language, and computer language. His team of students need to go over three different languages, which requires "translation" among the three languages. As this book was written to teach his research group how to translate, this book will also be useful for anyone who needs to learn how to translate in a similar situation.





The Julia Language is as fast as C, as convenient as MATLAB, and as general as Python with a flexible algebraic modeling language for mathematical optimization problems. With the great support from Julia developers, especially the developers of the JuMP—Julia for Mathematical Programming—package, Julia makes a perfect tool for students and professionals in operations research and related areas such as industrial engineering, management science, transportation engineering, economics, and regional science.





Table of Contents


1. Introduction and Installation


2. Simple Linear Optimization


3. Basics of the Julia Language


4. Selected Topics in Numerical Methods


5. The Simplex Method


6. Network Optimization Problems


7. Interior Point Methods


8. Nonlinear Optimization Problems


9. Monte Carlo Methods


10. Lagrangian Relaxation


11. Complementarity Problems


12. Parameters in Optimization Solvers








For more information, visit:



<a href="https://www.chkwon.net/julia">https://www.chkwon.net/julia</a>