Claudia Archetti is Associate Professor in Operations Research. She is member of the Operations Management & Operations Research (OMOR) Research Cluster. She teaches Decision Analysis, Optimal Decision Making, Advanced Optimization and Math Refreshing in ESSEC MSc and PhD programs. Prior to joining ESSEC in 2019, she was appointed at the University of Brescia as Assistant Professor in 2005 and as Associate Professor in 2014. Research interests of Claudia Archetti include models and algorithms for vehicle routing problems; mixed integer mathematical programming models for the minimization of the sum of inventory and transportation costs in logistic networks; exact and heuristic algorithms for supply-chain management; reoptimization of combinatorial optimization problems. Claudia Archetti has carried out the scientific activity in collaboration with Italian and foreign colleagues and published joint papers with some of the best researchers at the international level. She is author of more than 60 papers in international journals. She was Area Editor of Computers and Operations Research. She is Associate Editor of Transportation Science and of Networks and member of the Editorial Board of European Journal of Operational Research. She is currently VIP3 of EURO, the Association of European Operational Research Societies, in charge of publications and communication. Click here for the full list of publications, seminars, conferences and projects. Click here for Google Scholar profile.
Mobility problems involve transporting users from their origin to the desired destination. As such, they planning the itinerary of vehicles that are used for the service. We will focus on mobility services performed by buses and/or minibuses which, contrary to tram or metro, are not forced to follow the path determined by the related network. In this case, the problem of determining the trips of the buses corresponds to a routing problem with pickup and deliveries or to a Dial-A-Ride Problem (DARP) (this last terminology being the most commonly used in the mobility literature).
We will investigate different Mixed Integer Linear Problem formulations (MILPs) for routing problems in general, showing the advantages and the drawbacks of each of them. We will then move to formulations for the DARP. In addition, we will present ways to strengthen the formulations, namely through valid inequalities. Finally, we will show how MILPs can be used heuristically to build solution approaches capable of handling instances of larger size than the ones which are typically solved through exact approaches, avoiding, anyway, the burden of building ad-hoc heuristic or meta-heuristic algorithms. In particular, we will present different ways of building “easy to implement” matheuristics on top of a MILP formulations.
Maximilian Schiffer is Assistant Professor of Operations and Supply Chain Management at TUM School of Management, Technical University of Munich. Before joining TU Munich, he was a Visiting Postdoctoral Scholar at Stanford University and a Postdoctoral Scholar at RWTH Aachen University. Further, he is an Associate Member of the GERAD. He received a Ph.D. degree in Operations Research from RWTH Aachen University in 2017. Maximilian’s expertise lies in in the field of Operations Research and Management Science, specifically in Dynamic Programming, (Mixed) Integer Programming, Metaheuristics, Robust Optimization, as well as Machine Learning and Forecasting, applied to a variety of complex application fields, e.g., Transportation Problems, Supply Chains, Production Networks, and Big Data. His research on electric vehicles and logistics networks with intermediate stops has been awarded with numerous prizes, e.g., the INFORMS TSL Dissertation Prize and the GOR Doctoral Dissertation Prize. Currently, Maximilian’s research focuses on the development of Operations Research and Prescriptive Analytics methods to solve central societal problems, especially in the field of mobility and transportation. To this end he focuses on electric vehicles, autonomous mobility on demand systems, and inter and multi-modal transportation, including multi-stakeholder perspectives. His interdisciplinary work in this field has been recognized beyond the field of Operations Research in Robotics and Transport Engineering, e.g., by a best paper award from the IEEE Conference on Intelligent Transportation Systems.
Marlin Ulmer is a Professor at the Business Department of the Technische Universität Braunschweig. He studied Mathematics in Göttingen and Swansea. His PhD-thesis at TU Braunschweig focused on the interface between Management Science, Mathematics, and Computer Science. It was awarded, amongst others, by the INFORMS TSL Society and the German OR Society. Marlin’s teaching and research interests comprise applications from the entire field of Urban Mobility and Logistics, Operations Research, Stochastic Optimization, Dynamic Decision Making, Approximate Dynamic Programming, and Machine Learning. He works with leading experts of these fields all over the world. Click here for his Google Scholar profile.
Many urban mobility and logistics applications experience information changes over time, for example, when new mobility demand is revealed. Companies can adapt their plans to the new information, and if possible, can already anticipate future information changes in their planning. The corresponding mathematical models are (stochastic and dynamic) sequential decision processes.
We will discuss how to define, model, and solve sequential decision problems. We will focus on a set of selected applications from the field of urban mobility and logistics, amongst others, bike-sharing systems, same-day delivery, and dynamic dial-a-ride. We will review and analyze the existing methodology for solving sequential decision problems, for example, simulation procedures and approximate dynamic programming. We will also discuss and evaluate the suitability of different methodology with respect to problem and data characteristics. The overall goal is to get an overview over the field’s terminology and methodological toolkit while also getting an idea how to choose the “right” method for a specific problem.
Thibaut Vidal is a professor at the department of Computer Science of the Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Brazil. Previously he was postdoctoral researcher at LIDS, Massachusetts Institute of Technology, USA. He obtained a joint Ph.D in Computer Science from the University of Montreal, Canada, and from Troyes University of Technology, France. His research interests concern combinatorial optimization, metaheuristics, integer programming and convex optimization, with applications in supply chain management, signal processing and machine learning. He has authored over 40 articles in journals such as "Operations Research", "Transportation Science", "SIAM Journal on Optimization", "European Journal of Operational Research" and “Computers & Operations Research”. Thibaut Vidal works as associate editor for the journal Transportation Science. He has received the best paper award of the Transportation Science and Logistics Section of INFORMS twice (in 2014 and 2016), as well as the EJOR best paper award in the category “Theory and Methodology” in 2016. In 2018, he received the Robert Faure prize from the French Operations Research and Decision Support Society. In PUC-Rio he usually teaches discrete mathematics, operations research, modeling, and metaheuristics at the undergraduate and graduate level. Click here for his Google Scholar profile.
Vehicle routing problems have been the focus of extensive research over the past sixty years, driven by their economic importance and their theoretical interest. The diversity of their applications has motivated the study of a multitude of problem variants. In this talk, we will review some emerging VRP variants and heuristic solution techniques which are developed to tackle them. We will study the close connections between the structure of the problem decision sets and the solution methods, showing how heuristics can effectively perform a search in a reduced space defined by fewer groups of decision variables. Finally, we discuss recent research perspectives connecting machine learning, pattern extraction and local searches.
We will have a small get-together on the first evening at the TUM campus, allowing you to meet your fellow participants.
Dutch Treat Dinner:
We randomly assign all participants in small groups (4-6 people each), and reserve a table in a restaurant in downtown Heilbronn for you.
The wine tasting will take place at the winery "Fischer" just outside Heilbronn. After a guided hike through the vineyard, we will try three different wines and one sparkling wine, served with a small snack buffet. The bus will leave at 5PM outside the university, and will bring us back there around 9PM.
The conference dinner will take place at the "Insel-Hotel" in downtown Heilbronn. Details tba
Individual Discussions with Speakers:
Participants will have the option to discuss their research with the speakers. We would like to ask all participants to provide us with a ranked list of whom you want to speak with. As slots are limited, we cannot guarantee that every participant can talk in depth with all speakers.
We invite scholars currently pursuing a PhD in Operations Research, Transportation Science or related fields to apply for the summer school. The number of participants is limited to 40. Please send the following documents to firstname.lastname@example.org until March 31st 2020:
- Research Summary (at most 1 page describing your PhD project)
- Filled Registration Form
The summer school is mainly funded by TUM School of Management, but we require all participants to pay a fee of 150€ to cover expenses related to the social program (wine tasting, conference dinner).
- February 15th, 2020: application opens
- March 31st, 2020: application closes
- April 9th, 2020: notification of acceptance
- May 31st, 2020: registration closes for accepted participants
- July 27th-July 31st, 2020: PhD summer school
The summer school will take place in downtown Heilbronn (TUM Bildungscampus), there are several hotels within walking distance. We put a hold to rooms at the IBIS Hotel Heilbronn City for 72€/night including breakfast.
Heilbronn is situated in the German state Baden-Wurttemberg, 50km North of Stuttgart. The nearest airports are Stuttgart, Frankfurt and Munich. The best way to get to Heilbronn is the regional train from either Stuttgart, Mannheim or Wuerzburg.
The Summer School "Digital Transformation of Mobility Systems - OR Models and Methods" is organized by
- Prof. Rainer Kolisch
- Prof. Maximilian Schiffer
- Richard Littmann
- Layla Martin
- Janice Au
If you have any further questions, please do not hesitate to contact us: email@example.com