This event is reserved for GERAD members and their industrial partners. Registration is required.

The Large auditorium – GardaWorld is located on the 4th floor of the HEC Montréal's Hélène-Desmarais Building.

14:00  Mot de bienvenue d'Olivier Bahn

14:05 Sébastien Le Digabel, Polytechnique Montréal
Blackbox optimization: 15 years of progress with MADS and NOMAD
Blackbox optimization (BBO) arises when the problem is based on a blackbox: a simulation that may fail to evaluate, be time-consuming, or be contaminated by noise, and whose derivatives are unavailable. The first part of this presentation introduces BBO, some applications, and the main families of derivative-free methods, with a focus on the Mesh Adaptive Direct Search (MADS) algorithm. The second part reviews the progress made by our team over the last 15 years on MADS and the NOMAD software package.

14:35   Xiaozhe Wang, McGill University
Towards Reliable and Resilient Power Grids: Uncertainty Quantification and Data-Driven Decision-Making
The transition toward zero-emission power grids introduces growing uncertainties arising from renewable energy integration, extreme weather events, and emerging large loads. These uncertainties pose significant challenges to power system security and resilience, calling for computationally efficient approaches that can quantify risks and support informed decision-making.

This talk presents a data-driven uncertainty quantification framework based on polynomial chaos expansion (PCE) for probabilistic power system assessment. By leveraging historical and simulated data without requiring explicit assumptions about uncertainty distributions, the proposed approach achieves accuracy comparable to conventional Monte Carlo simulation at substantially reduced computational cost. Its non-intrusive nature enables integration with existing power system analysis tools, while global sensitivity analysis provides insights into the key factors driving system risks. Applications to probabilistic available transfer capability assessment and extreme-weather resilience evaluation will be presented. In particular, the results illustrate how uncertainty quantification can inform secure power transfer limits, identify critical infrastructure, and guide targeted hardening and proactive resilience planning.

15:05 Janosch Ortmann, UQAM
Collaborative routing for organic food distribution
In this talk I will discuss collaborative routing orchestration for organic food distribution. This is inspired by an ongoing collaboration with a regional organic food network in Quebec. The aim is to integrate hub selection, vehicle routing and synchronisation decisions under strict time and perishability constraints to coordinate multiple independent producers and food banks sharing logistics resources. I will introduce the problem and discuss solution approaches for the deterministic case, where all information is assumed to be known ahead of time. In particular, I will present a decomposition framework which splits the sequencing and timing decisions and allows us to solve realistic-sized instances. I will then briefly discuss the additional challenges that arise when uncertainty is explicitly modelled.

The presentation is based on ongoing and completed joint work with Ana María Anaya-Arenas, Camila Gómez López, Walid Klibi and Daniel Ocampo.

15:35   Coffee Break

16:00   Carolina Osorio, HEC Montréal
Accounting for input uncertainty in our models and in the field: the case of demand uncertainty for urban transportation problems
In urban transportation, the problem of estimating travel demand is a core and critical problem. Once estimated, travel demand is used to inform key investments such as road network expansion and maintenance. The main challenge in tackling this estimation problem in practice is that only spatially sparse traffic field data is available. This leads to an underdetermined problem, meaning that there are a number of travel demand solutions that provide statistically equivalent fit to the field data. Accounting for, and quantifying, this uncertainty or underdetermination is essential to provide robust urban investment recommendations. In this talk, we present various probabilistic methods to quantify uncertainty for such high-dimensional problems. We showcase their applications on various road networks. We discuss the implications of their use for transportation practice and articulate various open questions in the field.

16:30  Antoine Legrain, Polytechnique Montréal
Simulate to decide: real-time optimization from the lab to the field
Transportation systems increasingly operate in real time: data streams in continuously and decisions must be made within seconds. I will present a simulator that reproduces a full network (vehicles, passengers, disruptions) and lets any optimization algorithm be evaluated on real data before deployment. I will illustrate it with two completed projects, real-time synchronization of bus transfers with the STL and the RTC, and anytime column generation for large-scale on-demand transport, and then with two projects just getting under way: dynamic ambulance deployment with Urgences-santé and the Great Lakes project.

17:00 - 19:00  Cocktail in the Luc-Poirier Lounge 6th floor