Γ-opt

Γ-opt

Group of Applied Mathematical Modelling and Optimisation

Aalto University

About us

The Γ-opt (reads gamma-opt) research group is a part of the Systems Analysis Laboratory in the Department of Mathematics and Systems Analysis at Aalto University.

We develop research in the fields of Operations Research and Management Science, with emphasis on Mathematical programming and Optimisation under uncertatinty. The appliations of our research includes areas such as Energy systems, Production and operations planning, Supply chain management, and Humanitarian and healthcare logistics.

Follow the updates of our group on our LinkedIn page.

If you are interested in positions, collaborations or exchange opportunities, please contact Fabricio Oliveira.

Research topics

decision_making
Modelling decision-making and uncertainty

  • Endogenous uncertainty
  • Robust optimisation
  • Stochastic programming
  • Machine learning & surrogate modelling

decomposition
Efficient formulation and solution methods

  • Convexification techniques
  • Cutting planes & column generation
  • Lagrangian-based decomposition methods
  • Parallelisation

Application areas

energy
Energy systems
production
Production and operations planning
supply_chain
Supply chain management
humanitarian_logistics
Humanitarian and healthcare logistics

Projects

.js-id-current
EasyDR - Enabling demand response through easy to use open source approach
  • Funding organisation: Academy of Finland
  • Funding period: Jan 2022 - Dec 2024
  • Summary: This project attempts to enable large scale flexibility of electricity consumption at the residential scale, which in turn will allow more variable power generation, such as wind power and photovoltaics, to be cost effectively integrated in the energy system.
EasyDR - Enabling demand response through easy to use open source approach
Decision Programming: A Stochastic Optimization Framework for Multi-Stage Decision Problems
  • Funding Organisation: Academy of Finland
  • Funding period: Sep 2020 - Aug 2024
  • Summary: The project will further develop the decision programming framework as a methodology for modelling and solving multi-stage decision problems under uncertainty
Decision Programming: A Stochastic Optimization Framework for Multi-Stage Decision Problems