Retour aux activités
Séminaire “Un(e) chercheur(-euse) du GERAD vous parle!”

Learning and Stochastic Optimization for Industrial Mining Complexes


24 avr. 2024   11h00 — 12h00

Yassine Yaakoubi Université McGill, Canada

Yassine Yaakoubi

Présentation sur YouTube.

Decision-making in complex and/or stochastic settings, such as industrial mining complexes, presents significant challenges across various sectors. This seminar will delve into a novel solution approach that integrates machine learning and optimization for mineral supply/value chains under supply and demand uncertainties. We will explore three interconnected paradigm shifts: 1) data-driven hyper-heuristics with a heuristic search tree and self-adaptive framework; 2) smart lifelong learning context-aware solvers, with a hyper-heuristic for dynamic mining complex modeling, neural diving policy for heuristic selection, and neural branching policy with a soft branching strategy; and 3) a distributional perspective for warm-starting, using historical solutions and graphical models for initial production schedules. The performance of the proposed approach will be demonstrated through computational results and case studies, showcasing up to three orders of magnitude reductions in primal suboptimality and execution times, and increased robustness in solutions yielding up to 40% higher net present values. Finally, we will discuss insights, potential limitations, and future research directions in developing robust, reasoning, and responsible decision-support systems for industrial-scale uncertain environments.

Olivier Bahn responsable


Activité hybride au GERAD
Zoom et salle 4488
Pavillon André-Aisenstadt
Campus de l'Université de Montréal
2920, chemin de la Tour

Montréal Québec H3T 1J4

Organisme associé