60 citations · 163 across the 27 of their papers we have counts for
27 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…
Dynamic Neighborhood Construction for Structured Large Discrete Action Spaces
Fabian Akkerman, Julius Luy, Wouter van Heeswijk +1
Large discrete action spaces (LDAS) remain a central challenge in reinforcement learning. Existing solution approaches can handle unstructured LDAS with up to a few million actions…
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…
Learning-based Online Optimization for Autonomous Mobility-on-Demand Fleet Control
Kai Jungel, Axel Parmentier, Maximilian Schiffer +1
Autonomous mobility-on-demand systems are a viable alternative to mitigate many transportation-related externalities in cities, such as rising vehicle volumes in urban areas and tr…
Driver-aware charging infrastructure design
Stefan Kober, Maximilian Schiffer, Stephan Sorgatz +1
Public charging infrastructure plays a crucial role in the context of electrifying the private mobility sector in particular for urban regions. Against this background, we develop…
Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems
Tobias Enders, James Harrison, Marco Pavone +1
We consider the sequential decision-making problem of making proactive request assignment and rejection decisions for a profit-maximizing operator of an autonomous mobility on dema…
Optimizing intermodal transportation networks at scale via column generation
Benedikt Lienkamp, Maximilian Schiffer
In light of the need for design and analysis of intermodal transportation systems, we propose an algorithmic framework to determine the system optimum of an intermodal transportati…
Bilevel Optimization for Feature Selection in the Data-Driven Newsvendor Problem
Breno Serrano, Stefan Minner, Maximilian Schiffer +1
We study the feature-based newsvendor problem, in which a decision-maker has access to historical data consisting of demand observations and exogenous features. In this setting, we…
Robust Charging Network Planning for Metropolitan Taxi Fleets
Gregor Godbersen, Rainer Kolisch, Maximilian Schiffer
We study the robust charging station location problem for a large-scale commercial taxi fleet. Vehicles within the fleet coordinate on charging operations but not on customer acqui…
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…
Driver Routing and Scheduling with Synchronization Constraints
Pia Ammann, Rainer Kolisch, Maximilian Schiffer
This paper investigates a novel type of driver routing and scheduling problem motivated by a practical application in long-distance bus networks. A key difference from other crew s…
Designing Tractable Piecewise Affine Policies for Multi-Stage Adjustable Robust Optimization
Simon Thomä, Grit Walther, Maximilian Schiffer
We study piecewise affine policies for multi-stage adjustable robust optimization (ARO) problems with non-negative right-hand side uncertainty. First, we construct new dominating u…
Optimal Decision Diagrams for Classification
Alexandre M. Florio, Pedro Martins, Maximilian Schiffer +2
Decision diagrams for classification have some notable advantages over decision trees, as their internal connections can be determined at training time and their width is not bound…
Coordinated Charging Station Search in Stochastic Environments: A Multi-Agent Approach
Marianne Guillet, Maximilian Schiffer
Range and charge anxiety remain essential barriers to a faster electric vehicle market diffusion. To this end, quickly and reliably finding suitable charging stations may foster an…
Electric vehicle charge scheduling with flexible service operations
Patrick Sean Klein, Maximilian Schiffer
Operators who deploy large fleets of electric vehicles often face a challenging charge scheduling problem. Specifically, time-ineffective recharging operations limit the profitabil…
Online Traffic Routing: Deterministic Limits and Data-driven Enhancements
Devansh Jalota, Dario Paccagnan, Maximilian Schiffer +1
Over the past decade, GPS enabled traffic applications, such as Google Maps and Waze, have become ubiquitous and have had a significant influence on billions of daily commuters' tr…
On the Interplay between Self-Driving Cars and Public Transportation
Nicolas Lanzetti, Maximilian Schiffer, Michael Ostrovsky +1
Cities worldwide struggle with overloaded transportation systems and their externalities. The emerging autonomous transportation technology has the potential to alleviate these iss…
The Customer is Always Right: Customer-Centered Pooling for Ride-Hailing Systems
Paul Karaenke, Maximilian Schiffer, Stefan Waldherr
Today's ride-hailing systems experienced significant growth and ride-pooling promises to allow for efficient and sustainable on-demand transportation. However, efficient ride-pooli…
A Concise Guide on the Integration of Battery Electric Buses into Urban Bus Networks
Nicolas Dirks, Dennis Wagner, Maximilian Schiffer +1
With the increasing market penetration of battery-electric buses into urban bus networks, practitioners face many novel planning problems. As a result, the interest in optimization…
On the Integration of Battery Electric Buses into Urban Bus Networks
Nicolas Dirks, Maximilian Schiffer, Grit Walther
Cities all around the world struggle with urban air quality due to transportation related emissions. In public transport networks, replacing internal combustion engine buses by ele…
Electric Vehicle Charging Station Search in Stochastic Environments
Marianne Guillet, Gerhard Hiermann, Alexander Kröller +1
Electric vehicles are a central component of future mobility systems as they promise to reduce local noxious and fine dust emissions and CO2 emissions, if fed by clean energy sourc…
Online Hypergraph Matching with Delays
Marco Pavone, Amin Saberi, Maximilian Schiffer +1
We study an online hypergraph matching problem with delays, motivated by ridesharing applications. In this model, users enter a marketplace sequentially, and are willing to wait up…
Born-Again Tree Ensembles
Thibaut Vidal, Toni Pacheco, Maximilian Schiffer
The use of machine learning algorithms in finance, medicine, and criminal justice can deeply impact human lives. As a consequence, research into interpretable machine learning has…