Course description
Optimization: Principles and Algorithms - Network and Discrete Optimization
Introduction to the mathematical concept of networks, and to two important optimization problems on networks: the transshipment problem and the shortest path problem. Short introduction to the modeling power of discrete optimization, with reference to classical problems. Introduction to the branch and bound algorithm, and the concept of cuts.
Upcoming start dates
Who should attend?
Prerequisites:
The course assumes that you are familiar with linear optimization. We advise you to follow the companion course on that topic if it is not the case.
The knowledge of the programming language Python is an asset to learn the details of the algorithms. However, it is possible to follow the course without programming at all.
Training content
- Networks: you will be introduced to the mathematical formalism of graphs and networks.
- Transhipment: you will learn about the transhipment problem (also called "minimum cost flow problem"), its properties, and some special instances.
- Shortest path: you will learn about algorithms to find the shortest path in a network.
- Discrete optimization: you will learn how to specify a discrete optimization problem.
- Exact methods for discrete optimization: you will be introduced to two algorithms to solve discrete optimization problems.
Course delivery details
This course is offered through Swiss Federal Institute of Technology Lausanne, a partner institute of EdX.
6-8 hours per week
Costs
- Verified Track -$49
- Audit Track - Free
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