Semi-supervised clustering is a learning approach that primarily relies on unlabeled data but incorporates some prior information to improve the clustering r...

The Batch Pan Scheduling Problem represents a major operational challenge in white sugar refineries, where production planning must balance throughput object...

Topological indices are graph-theoretic descriptors that play a crucial role in mathematical chemistry, capturing the structural characteristics of molecules...

This paper investigates the Collaborative Routing Orchestration for Organic Food Distribution Problem (CRO-FDP), a two-echelon collaborative distribution n...

The CRM, IVADO, and GERAD organized jointly the Fifteenth Montreal Industrial Problem Solving Workshop, which was held at HEC Montréal on June 2-6, 2025. We ...

This multi-model analysis examines the prospects of hydrogen in the Canadian and German energy systems, and particularly of hydrogen exports from Canada to...

The reformulation-linearization technique (RLT) is a well-established framework for generating hierarchies of linear programming (LP) relaxations for a wide ...

As the need for interpretable machine learning continues to grow, we propose a novel post-clustering method to generate counterfactual explanations for clust...

In addressing climate change, countries rely on two primary strategies: mitigation, which aims to reduce greenhouse gas emissions, and adaptation, which seek...

We introduce Spatial Pattern Regression (SPR), a method to generate gridded historical meteorological data for climate adaptation. SPR operates in two steps:...

Large-scale distributed wireless networks provide infrastructure-free and cost-effective connectivity, supporting applications from disaster recovery to glob...

Chemical graphs are simple undirected connected graphs, where vertices represent atoms in a molecule and edges represent chemical bonds. A degree-based topo...

The growing reliance on power electronics introduces new challenges requiring detailed time-domain analyses with fast and accurate circuit simulation tools...

For continuing tasks, average cost Markov decision processes have well- documented value and can be solved using efficient algorithms. However, it explici...

Benchmarking is essential for assessing the effectiveness of optimization algorithms. This is especially true in derivative-free optimization, where target ...

Hydropower generation plays a crucial role in the global energy landscape, offering a renewable and sustainable source of electricity. Accurate forecasting o...

This work presents a new strategy to virtual bidding based on distributionally robust optimization (DRO) using a Wasserstein distance. Virtual bidding, a mec...

The \(p\)-median problem is a classical location problem where the goal is to select \(p\) facilities while minimizing the sum of distances from each loc...

Local search methods start from a feasible solution and improve it by successive minor modifications until a solution that cannot be further improved is enco...

This paper introduces a new approach to nurse scheduling that integrates employee well-being into the decision-making process. A random forest regressor is t...