The \(k\)-means algorithm is one of the most widely used methods for solving the minimum sum-of-squares clustering (MSSC) problem, but it is well known to ...

Predicting the state of the weather, from tracking hurricanes and thunderstorms to assessing daily temperatures, is of crucial importance. Over the past deca...

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...