Material for the EPFL course MATH-265 "Introduction to optimization and operations research"
Exercises for each week should be done in the order that you prefer based on the lectures that you have followed.
Note: If lectures have not covered the subject of the exercise, you can skip them and do them the following week.
In this document, we explain week by week the planned exercises in Jupyter Notebook.
- Coola Coola --> lab01
- Karush-Kuhn-Tucker --> lab04
- Standard form --> lab05
- Existence --> lab06
- projectile 1
- projectile 2
- Active constraints --> lab06
- Feasible directions --> lab02
- Vertices and feasible solutions --> lab03
- Basic directions -> lab04
- lab01 Feasibility
- Reduced costs --> lab05
- Redundant constraints --> lab07
- Pivoting --> lab05
- Simplex algorithm --> lab03
- Simplex tableau (describe the elements) --> lab04
- Multiple choice questions --> lab08
- lab01: enumeration
- lab02: graphical solution
- lab06: simplex tableau
- Initial tableau --> lab07
- Duality and feasibility --> lab01
- Dual problem --> lab02
- Complementarity slackness --> lab03
- Network properties --> lab01
- Flows and divergences --> lab02
- Trees --> lab03
- Formulation and standard form --> lab03
- Optimality conditions --> lab04
- Total unimodularity --> lab01
- Shortest path --> lab02
- Maximum flow --> lab05
- Transportation --> lab06
- Buying train tickets --> lab07
- Generic algorithm --> lab01
- Bellman subnetwork --> lab02
- Dijkstra algorithm --> lab03
- PERT --> lab05
- Branch and bound --> lab01
- Modeling --> lab02
- Set covering --> lob03
- Traveling salesman problem --> lab04
- B & Bound integer problem --> lab01
- Relaxation --> lab05
- First Wolfe --> lab01
- Second Wolfe --> lab02
- Newton local --> lab03
- Preconditioning --> lab04
- Line search --> lab06
- Multiple choice questions --> lab07
