LP and MILP

ISE 3200 Linear and Integer Programming

In this course we will show that linear programming (LP) problems are important for industry, explain how to formulate such problems, how to solve them and how to interpret the results. We will do likewise with mixed-integer linear programming (MILP) problems.

After successfully completing this course, you will be capable of analyzing relevant industry problem by formulating them as LP or MILP problems, solving them and interpreting the results obtained.

Contents: 

0. Welcome:

01 Welcome to ISE 3200

1. Linear programming:

1 LP real world examples

2 LP formulating problems

3 LP BFSs and optimality

4 LP a clever partition

5 LP the Simplex method

6 LP sensitivity

7 LP duality

2. Mixed integer linear programming:

1 MILP real world examples

2 MILP formulating problems

3 MILP linearizing nonlinearities

4 MILP solving via B&B

5 MILP solving via cuts

3. Homeworks:

Homework 1 — LP formulation

Homework 2 — LP solution

Homework 3 — LP analysis

Homework 4 — MILP formulation

4. Midterm Exams:

2018-ISE3200Fall2018Mid

2019-ISE3200Fall2019Mid

2020-ISE3200Fall2020Mid

5. Final Exams:

2018-ISE3200Fall2018Final

2019-ISE3200Fall2019Final

2020-ISE3200Fall2020Final

Textbook:

R. Sioshansi, A. J. Conejo, Optimization in Engineering. Models and Algorithms. Springer, New York, New York, 2017.