IVADO is supporting this research program with $1.2M as part of our Strategic Research Funding Program launched in 2021. We invite you to visit the program’s main page to view its objectives and better understand the process that supported this project.

Program description

Nearly all decision problems involve some form of uncertainty. This is especially true in supply chains where, e.g., demand, cost, capacity, and travel time’s high variability considerably complicate the planning of procurement, production, distribution, and service activities. Due to constantly evolving environments and the high frequency of data acquisition, classical decision-making that is based on training models, validating them, to finally optimize decisions does not suffice anymore. This research program aims at developing new methods for making the most effective and adaptive use of data in decision-making. It is founded on modern optimization and machine learning perspectives that encompasses developments in deep reinforcement/end-to-end learning, risk averse decision theory, and contextual/distributionally robust optimization. Its mission is three-fold: (i) develop the next generation of methods to deal with uncertainty in data-driven risk-aware optimization models by integrating machine learning; (ii) identify scientifically challenging and high-impact opportunities for improving robustness in supply chains; and finally (iii) stimulate the integration of stochastic optimization models among our partners while defining use cases that will guide future methodological advances. Overall, this program envisions a virtuous cycle of scientific discoveries that are both fueled by and transformative for an important sector of the Canadian economy.

Principal Investigators

Erick Delage

Full Professor

HEC Montréal, GERAD

Yossiri Adulyasak

Associate Professor

HEC Montréal, GERAD

Emma Frejinger

Associate Professor

Université de Montréal, CIRRELT

Useful links

Resources related to this program will appear here.

Press review

Articles and interviews related to this program will appear here.

Call for postdoctoral project proposals

Area of research: Integrated Machine Learning and Optimization for Decision Making under Uncertainty

Type of research: fundamental or applied

Type of program: support for postdoctoral fellows in research teams

Priority fields: data-driven optimization, contextual optimization, stochastic programming, robust optimization, supply chain applications

$35,000 for one year will be awarded to each selected project to provide partial support for a postdoctoral fellow in a research team. There is funding for a maximum of four projects. Projects can apply for a renewal after the first year.

Submission deadline: May 31st, 2022, 9 a.m. EDT.

Complete details for this call available in this PDF DOCUMENT.

NB: A SPECIAL SESSION of OPTIMIZATION DAYS 2022 (HEC Montréal, 16-18 May, 2022) will be dedicated to presenting and discussing this call for proposals and IVADO’s Strategic Research Program in Integrated Machine Learning and Optimization for Decision Making under Uncertainty.


We encourage you to contact us for any additional information or questions related to this program. Please use this email and we will respond to you as soon as possible.