3 citations · 6 across the 4 of their papers we have counts for
4 papers
Ambulance Demand Prediction via Convolutional Neural Networks
Maximiliane Rautenstrauß, Maximilian Schiffer
Minimizing response times is crucial for emergency medical services to reduce patients' waiting times and to increase their survival rates. Many models exist to optimize operationa…
Combinatorial Optimization enriched Machine Learning to solve the Dynamic Vehicle Routing Problem with Time Windows
Léo Baty, Kai Jungel, Patrick S. Klein +2
With the rise of e-commerce and increasing customer requirements, logistics service providers face a new complexity in their daily planning, mainly due to efficiently handling same…
Coordinating charging request allocation between self-interested navigation service platforms
Marianne Guillet, Maximilian Schiffer
Current electric vehicle market trends indicate an increasing adoption rate across several countries. To meet the expected growing charging demand, it is necessary to scale up the…
Support Vector Machines with the Hard-Margin Loss: Optimal Training via Combinatorial Benders' Cuts
Ítalo Santana, Breno Serrano, Maximilian Schiffer +1
The classical hinge-loss support vector machines (SVMs) model is sensitive to outlier observations due to the unboundedness of its loss function. To circumvent this issue, recent s…