The objective of this course is to introduce participants to the fundamentals of optimization techniques and their applications across various fields, highlighting the competitive advantages these methods provide. By the end of the course, students will be able to identify and formulate different types of optimization problems, such as linear programming (LP), mixed integer linear programming (MILP), and non-linear programming (NLP). They will also gain hands-on experience solving optimization problems using Excel’s solver, applying their skills to a real-world case study.
Learning outcomes
Upon the completion of the course, the participant will
- Acquire the basics of the use of optimization techniques on different fields of application and how these techniques provide a competitive advantage.
- Identify different optimization problems in terms of their mathematical formulation, e.g. linear programming (LP), mixed integer linear programming (MILP), non-linear programming (NLP), etc.
- Know how to use the solver of Excel to solve optimization problems.
About Project EAGLE
The course is developed under the framework of the EU-funded EAGLE project, an initiative that aims to contribute to development of vibrant European education communities and works with a range of business partners to identify existing skill/knowledge gaps and address them. The project is specifically dedicated to bringing concrete improvements for SMEs.
Now that we have sparked your interest, you’re free to explore this course – head over to project EAGLE’s website to find out more.
Source: European Digital Skills & Jobs Platform
