Delivery mode
Online
Estimated study time: 27 hours
Location
E-learning environment
Language
English
Scope
1 ECTS
Fundamentals of Mathematical Optimization
Make better decisions with the power of mathematical modelling
How can we make the best possible decisions when resources are limited and trade-offs are inevitable? This self-paced online course introduces the fundamentals of mathematical optimisation and how it can be used to support decision-making in real-world contexts.
Fundamentals of Mathematical Optimization teaches you how to represent complex problems as mathematical models and solve them using optimization techniques. The course covers linear, integer, and nonlinear optimization, with a strong focus on practical modelling choices and real-life applications in areas such as transport, health, and energy.
After completing the course, you will have a solid understanding of how to frame complex decisions, balance competing goals, and critically assess what “optimal” really means.
Benefits
The course is built around three key themes that guide your learning journey:
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Why do you need a mathematical optimisation model? Understand the value of optimisation in solving complex, real-world problems.
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What is mathematical optimisation? Learn the core concepts and techniques that underpin optimisation models.
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Mathematical programming. Dive into the practical tools and methods used to formulate and solve optimisation problems.
These themes provide a foundation for developing the ability to model, analyse, and solve decision-making problems in a wide range of domains.
Learning Outcomes
After completing the course, you will be able to:
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Recognize the role of optimization in addressing societal challenges such as transport, health, and energy
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Understand the fundamental elements of an optimization model and how they support decision-making
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Formulate real-world problems in a way that makes them suitable for mathematical optimization modelling
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Evaluate how optimization informs practical choices, while acknowledging its assumptions and limitations
For
The course is designed for higher education students, early-career professionals, and advanced professionals who want to understand how mathematical optimization can be applied in practice. It is especially relevant for professionals and academics seeking to develop their skills in applying optimization and mathematical programming to real-world decision-making.
Content and Schedule
The course takes approximately 27 hours to complete and is equivalent to 1 ECTS. It consists of video lectures, along with quizzes and modelling exercises that support learning.
You can complete the course at your own pace, either by spreading the content over several weeks or by following a more focused schedule. To finish the course and receive a certificate, you need to watch all videos and complete the quizzes with a minimum score of 75 percent.
Modules
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Functions and optimization
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Mathematical programming
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Mathematical programming models: examples
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Symbolic formulation
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Mathematical programming models: more examples
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Modelling integer decisions
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Mathematical programming models: (mixed-)integer examples
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Multi-objective optimization
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Nonlinear optimization
Instructor
Fabricio Oliveira
Dr. Oliveira is an associate professor of operations research at Technical University of Denmark. He has extensive international academic and industry experience in optimization. He has held positions at Aalto University, Houston Analytics, Carnegie Mellon University, RMIT University, and PUC-Rio. His research focuses on applying optimization under uncertainty to solve complex production planning and supply chain management problems.
Program Fee and Registration
The fee for the Fundamentals of Mathematical Optimization online course is € 150 (+ VAT).
This program has adopted Aalto EE's new Customer ID, and it is delivered on Aalto Learning Experience Alex e-learning environment. Before ordering, please visit aaltoee.fi/customerid.
Program start