Optimization and Decision Systems (ODS)

The mission of this research group is to promote a modern vision of optimization and decision systems as cross-disciplinary areas intersecting Operations Research Engineering, Systems and Control Engineering, Computational Social Science and Quantitative Economics. The massive penetration of smart technology has transformed many engineering systems such as transportation, logistics, energy and security to name just a few. In all these contexts, one often observes a large number of machines and humans interacting with each other. Thus there is a need to redefine the boundaries of some engineering disciplines to accommodate both physical and socio-economic components. Control Engineering, the discipline which studies the ways in which one can control the evolution of a system is no exception. A core concept in control engineering is ‘feedback’ whereby a machine (the controller) gets measurements from sensors about the state of the system one wishes to control and sets the inputs to the system. In the presence of numerous machines and humans, one observes the humans turning into strategic players who learn the environment and make decisions knowing that the environment (which is constituted by the other players) is at the same time learning about them and will react accordingly. This takes the concept of feedback to the next level and opens the floor to a number of game theoretic aspects (learning, incentives, pricing) which contribute to the ‘modernization’ of systems and control engineering.

Among the goals of this research group is the one of developing and supporting novel engineering methods based on optimization, systems and control, and game theory to incentivise cooperation among selfish decision-makers in engineering applications. The main findings will address modelling / understanding of socio-technical systems in different applications domains including: Operations Research, Transportation, Logistics, Inventory Control, Cybersecurity, Pricing, Opinion dynamics and diffusion in Social Networks.

This research group will complement and support joint research especially with other two groups in ENTEG, Discrete Technology & Production Automation and Smart Manufacturing Systems

Research Staff

PhD Students