CO@Work 2024

Computational Optimization at Work

About

The summer school CO@Work 2024 will be held from September 16 to 27, 2024, at Zuse Institute Berlin and is organized jointly by TU Berlin, HTW Berlin, and Zuse Institute Berlin, and co-sponsored by MATH+, BMS, Forschungscampus MODAL, I²DAMO, GOR, DFG Priority Program 2298, COPT, d-fine, FICO, GAMS, and Gurobi.







This block course addresses everyone interested in the use of computational optimization and mathematical programming in concrete applications from practice, in particular advanced masters students, PhD students, and post-docs.

CO@Work2024 will be the seventh incarnation of this workshop series, and the fifth one being held in Berlin.

Schedule

The following is a tentative schedule, please note that some details could still change at this stage. On most days, we will have breaks 10:45-11:15, 12:45-14:15, and 15:45-16:15. For some talks, abstracts can already be revealed by clicking on the title of the talk.

Monday, 16.09.2024 Welcome and Introduction
15:30 Sebastian Pokutta Opening
15:40 Jens Schulz Welcome from the German OR Society

German Society of Operations Research is a non-profit organization with more than 1,000 members. GOR spreads the word about Operations Research throughout academia and practice as its key mission.
15:50 Annika Preuß-Vermeulen Berlin Mathematical School PhD program

The Berlin Mathematical School (BMS) is a joint graduate school of the mathematics departments of the three major Berlin universities, TU Berlin, FU Berlin, and HU Berlin, and the graduate school of the Cluster of Excellence MATH+. The BMS offers a course program in English, various events and mentoring opportunities and advice in non-academic issues. Besides striving for excellence, BMS is actively pursuing the goals of diversity in gender and country of origin for its student body.
16:00 Timo Berthold, Ambros Gleixner Organization of the Summer School
16:30 Martin Grötschel Optimization and OR: A Sketch of Historical Developments

If one looks back into recorded history or analyses archaeological findings, it is clear that humans have always tried to act, build, and work efficiently – subject to available knowledge and technology. OR and optimization seem to be genuine human features. I plan to briefly sketch some of these historical developments starting in antiquity, but my focus will be on the details of the advancements in optimization (in particular linear and integer programming) in the last 70 years. One part of my lecture will be staged as a quiz. For those interested in preparing for the quiz, some of the answers can be found in the book “Optimization Stories” that I edited in 2012. The PDF of this book can be downloaded from my homepage at https://www.zib.de/userpage//groetschel/publications/OptimizationStories.pdf or from the Webpage of Documenta Mathematica: https://www.elibm.org/article/10011477
17:30 Thorsten Koch Data Experiment
18:00 Welcome BBQ
Tuesday, 17.09.2024 Fundamentals of Linear Programming and Modelling
9:15 Ambros Gleixner Linear Programming & Polyhedral Theory
10:00 Julian Hall High Performance Computational Techniques for the Simplex Method

When families of related LP problems are to be solved, most notably as subproblems when solving MIPs, efficient implementations of the simplex algorithm are used. This lecture will discuss the reasons for this, and give an overview of the most important algorithmic variants and computational techniques for their implementation.
11:15 Qi Huangfu Linear Programming: Barrier and First Order Methods
12:00 Ambros Gleixner Aspects of MIP Modelling
14:15
-17:45
Bruno Vieira Tutorial: Basics of MIP Modelling
Wednesday, 18.09.2024 Fundamentals of Mixed Integer Programming
9:15 Timo Berthold MIP Solving: Branch-and-Bound
10:00 Timo Berthold MIP Solving: Cutting Planes
11:15 Timo Berthold MIP Solving: Primal Heuristics
12:00 Timo Berthold MIP Solving: Presolving
14:15
-17:45
Bruno Vieira Tutorial: Advanced MIP Modelling
Thursday, 19.09.2024 Advanced Mathematical Optimization
9:15 Ksenia Bestuzheva Global Optimization of Mixed-Integer Nonlinear Programs
10:00 Marc Pfetsch Solving Mixed-Integer Semidefinite Programs

Mixed-integer semidefinite programs deal with optimization subject to semidefinite constraints on matrix variables including integrality conditions. We review solving techniques for such problems. This includes presolving and heuristics. An implementation in SCIP-SDP will be demonstrated.
11:15 Ambros Gleixner Numerics in LP & MIP Solvers
12:00 Marco Lübbecke Branch-and-Price Crash Course

Decomposition and refomulation techniques (like Dantzig-Wolfe) can lead to MIP models with many variables. Even only the LP relaxations of such models need to be solved by column generation. We discuss column generation basics and options how to embed this into a branch-and-cut tree
14:15
-17:45
Mohammed Ghannam, Joao Dionisio Tutorial: Implementing Branch-and-Price
Friday, 20.09.2024 Interactive Optimization and Learning
9:15 Grégoire Montavon Explainable AI
10:00 Jannis Kurtz Deep Learning in Robust Optimization

Deep learning (DL) is one of the most popular approaches used for recent developments in the realm of Artificial Intelligence. On a high level, the goal in DL is to fit a neural network to available training data to solve classification or regression problems. In this talk we will study neural networks from a mixed-integer optimization perspective. We show that, under certain assumptions, the evaluation of an already trained neural network can be modeled as a mixed-integer linear problem. These trained neural networks can be used to support classical optimization tasks in different ways. The focus of this talk will be on robust optimization problems, where the goal is to find an optimal solution of an optimization problems which is robust against uncertainty in the problem parameters. We will show how MIP representations of neural networks can be used in robust optimization to speed up solution algorithms and model uncertainty sets.
11:15 Nicole Megow Learning-Augmented Algorithms for Scheduling

Uncertainty poses a significant challenge on scheduling and planning tasks, where jobs may have unknown processing times or unknown dependencies. However, assuming a complete lack of a priori information is overly pessimistic. With the rise of machine-learning methods and data-driven applications, access to predictions about input data or algorithmic actions becomes feasible. Yet, blindly trusting these predictions might lead to very poor solutions, due to the absence of quality guarantees.

In this talk, we explore recent advancements in the popular framework of Algorithms with Predictions, which integrates such error-prone predictions into online algorithm design. We examine various prediction models and error measures, showcasing learning-augmented algorithms for non-clairvoyant scheduling with strong error-dependent performance guarantees. We demonstrate the potential of imperfect predictions to enhance scheduling efficiency and address uncertainty in real-world scenarios.
12:00 Christoph Spiegel The Role of Machine Learning for Mathematics
14:15 Berkant Turan Tutorial: Hands-on Machine Learning
16:15-
17:45
Mathieu Besancon Tutorial: Hands-on Frank-Wolfe
19:00 Conference Dinner (Berlin TV Tower)
Saturday, 21.09.2024 Vehicle Routing
10:00 Eduardo Uchoa Exact Algorithms for Vehicle Routing: advances, challenges, and perspectives

The vehicle Routing Problem (VRP) is among the most widely studied problems in operations research and combinatorial optimization. The current state-of-the-art exact VRP algorithms employ a combination of column generation and cut separation, known as Branch-Cut-and-Price (BCP) algorithms. This presentation examines notable recent contributions made by various researchers in the field. Additionally, the talk showcases VRPSolver, a very flexible package that implements a BCP algorithm that achieves outstanding performance for many routing, packing, and scheduling problems. Furthermore, VRPSolverEasy, a recent Python application built on top of VRPSolver, is introduced. While heuristic algorithms are likely to remain the dominant approach for practical routing, the availability of exact solutions for reasonably sized instances opens up new possibilities.
10:45 Kai Hoppmann-Baum "Excuse me, Sir, we ordered 31 minutes ago!" - How to address time delays in food delivery
11:15 Thorsten Koch TBA
11:45 Lunch (ZIB Foyer)
12:45
-15:00
Milena Petkovic Computational Challenge Day 1
Sunday, 22.09.2024 Day off
Monday, 23.09.2024 Applied Machine Learning and Optimization
9:15 Jan Kronqvist Building upon MIP and non-smooth optimization to learn robust deep neural networks
10:00 Timo Berthold ML inside MIP solvers
11:15 Andrea Lodi TBA
12:00 Ruth Misener Optimal decision-making problems with trained surrogate models embedded

Several of our recent projects (and complementary projects by other groups worldwide) embed data-driven surrogate models into larger optimal decision-making problems. For example, with the chemicals company BASF, we considered solving inverse problems over trained graph neural networks to design new molecules. This presentation discusses some of the mathematical challenges and practical applications we have explored. We also mention software implementations and close with open challenges in the area.
14:15-
17:45
Milena Petkovic Computational Challenge Day 2
Tuesday, 24.09.2024 Excursions to Volkswagen and TESLA
Wednesday, 25.09.2024 Energy Systems
9:15 Milena Petkovic TBA
10:00 Inci Yüksel-Ergün Data Preprocessing and Data Quality Assessment for Energy System Optimization
11:15 Jaap Pedersen Quota Steiner Tree Problem and its Application on Wind Farm Planning
12:00 Stephanie Riedmüller Unit Commitment and Investment Planning for District Heating Networks
14:15-
17:45
Milena Petkovic Computational Challenge Day 3
Thursday, 26.09.2024 Traffic and Logistics
9:15 Ralf Borndörfer TBA
10:00 Niels Lindner Periodic timetable optimization in public transport
11:15 Daniel Rehfeldt Optimizing vehicle and crew schedules in public transport
12:00 Daniel Roth Using airline planning software to plan ICU personnel
14:15-
17:45
Milena Petkovic Computational Challenge Day 4
Friday, 27.09.2024 Industry Day
9:15 Zsolt Csizmádia TBA
9:45 Adele Goutes How to set optimal prices during a sales event steered by humans?
10:15 Jakob Witzig SAP Supply Chain Optimization
11:15 Anna Thünen, Jennifer Uebbing Optimization in practice: from long to short, from planning to operation of (power) grids
11:45 Felix Hennings Dimension Local Energy Hubs to Reduce Grid Congestion
12:15 Petra Bauer Mathematical Optimization @ Siemens

The research group "Operations Research for Decision Support" at Siemens Technology applies Mathematical Optimization to a broad variety of real-life problems from different Siemens domains such as industry, energy, mobility, or healthcare. This talk presents some facts and figures about Siemens, gives insights into the background and competences of our team as well as our everyday work, and showcases two projects, one about a check-in/be-out ticketing solution, the other about solar power plant layout optimization.
14:15 Justine Broihan Managing the Optimization Pipeline
14:45 Tim Januschowski TBA
15:15 Networking with Industry
16:15 Pawel Lichocki Combinatorial Optimization at Google: tools, solvers, and applications
16:45 Matthias Miltenberger Gurobi OptiMods - Painless Optimization Templates

One of the most important aspects of mathematical optimization and Operations Research is getting your data into a form that optimization solvers can understand and work with. The "art of modeling" as it is often referred to, can all too easily get in the way of actually solving the problem at hand. Gurobi's open-source OptiMods are data-driven Python APIs for different common optimization use cases. They enable practitioners and learners alike to compute solutions without requiring extensive modeling experience. This session presents the goals and design of the project and explains how to use and extend it. We will also give an insight into how the Gurobi Experts team works to get the most out of Gurobi for its customers.
17:15 Closing session
18:00 Farewell BBQ
Monday, 07.10.2024 Examination

The examination for all students that participated on-site and wish to obtain a 10 ECTS certificate will be held one week after the summer school, October 7, 15:00-17:00. The exam will be on-site for students from Berlin universities (in room MA004 at TU Berlin's math building) and remotely for other participants.

Speakers

  • Petra Bauer, Siemens AG
  • Mathieu Besancon, ZIB and Inria Grenoble
  • Timo Berthold, TU Berlin and FICO Xpress
  • Ksenia Bestuzheva, ZIB
  • Ralf Borndörfer, FU Berlin and ZIB
  • Justine Broihan, GAMS
  • Zsolt Csizmádia, Amazon
  • Joao Dionisio, Universidade do Porto
  • Mohammed Ghannam, HTW Berlin and felmo GmbH
  • Ambros Gleixner, HTW Berlin and ZIB
  • Adele Goutes, Zalando
  • Martin Grötschel, BBAW
  • Julian Hall, University of Edinburgh
  • Felix Hennings, Doing the Math
  • Qi Huangfu, Cardinal Operations
  • Kai Hoppmann-Baum, Delivery Hero
  • Tim Januschowski, Databricks
  • Thorsten Koch, TU Berlin and ZIB
  • Jan Kronqvist, KTH
  • Jannis Kurtz, University of Amsterdam
  • Pawel Lichocki, Google
  • Niels Lindner, FU Berlin and ZIB
  • Andrea Lodi, Cornell Tech
  • Marco Lübbecke, RWTH Aachen
  • Nicole Megow, University Bremen
  • Matthias Miltenberger, Gurobi Optimization
  • Ruth Misener, Imperial College London
  • Grégoire Montavon, FU Berlin
  • Jaap Pedersen, ZIB
  • Milena Petkovic, ZIB and Leibniz IKZ
  • Annika Preuß-Vermeulen, BMS
  • Marc Pfetsch, TU Darmstadt
  • Sebastian Pokutta, TU Berlin and ZIB
  • Daniel Rehfeldt, Optibus
  • Daniel Roth, Boeing
  • Jens Schulz, Gesellschaft für Operations Research e.V.
  • Christoph Spiegel, ZIB
  • Anna Thünen und Jennifer Uebbing, d-fine
  • Berkant Turan, ZIB
  • Eduardo Uchoa, Universidade Federal Fluminense
  • Bruno Vieira, FICO Xpress
  • Jakob Witzig, SAP
  • Janina Zittel, ZIB

Registration

There are good and bad news. The bad news first: The application for the in-person event is currently closed because we have reached our capacity limit. If spots become available, we will contact people on our waiting list. That being said, if you cannot join CO@Work for any unforeseen reasons, please let us know so we can pass your spot along.

The good news: There will be a limited (!) online version of CO@Work. Online participants will have the possibility to:

  • view all* lectures as a stream in a Zoom Webinar (*=provided the lecturer's permission)
  • ask questions via Zoom's Q&A capabilities
Online participants will not have the opportunity to:
  • join the hand's-on tutorials
  • participate in the networking events or the excursion
  • receive any ECTS certificates
  • enjoy late summer in sunny Berlin
If you would like to join CO@Work online, please register here:

Online participation is free. The registration fee for on-site participation will be 100 EUR per participant, waived for students from Berlin universities. The language of the course is English.

Accommodation

There are only few hotels within less than half an hour walking distance of ZIB, those are listed below. If those are booked, we recommend to look for accommodation close to the subway line U3, the bus line X83 or the bus line 101, all of which have a stop close to ZIB.
Please note that September 28/29 is the weekend of the Berlin Marathon, so it is probably a good idea to book as soon as possible, in particular if you wish to stay beyond the last Friday.


**** Seminaris CampusHotel Berlin
Address: Takustr. 39, 14195 Berlin
Web: https://www.seminaris.de/hotels/berlin/seminaris-campushotel-berlin
Getting to ZIB: 300 metres to walk

Apartment Hotel Dahlem
Address: Clayallee 150-152, 14195 Berlin
Web: https://www.apartment-hotel-berlin.de/en/the-hotel/
Getting to ZIB: 6 minutes by bus X83 plus 600 metres to walk OR 25 minutes to walk

*** Ravenna-Hotel Berlin
Address: Grunewaldstr. 8-9, 12165 Berlin
Web: https://www.novum-hotels.com/en/hotel-ravenna-berlin
Getting to ZIB: 3 minutes by bus X83 plus 400 metres to walk OR 20 minutes to walk

**** Hotel Steglitz International
Address: Albrechtstraße 2, 12165 Berlin
Web: https://www.si-hotel.com/
Getting to ZIB: 9 minutes by bus X83 plus 150 metres to walk

*** Hotel Pension Dahlem
Address: Unter den Eichen 89A, 12205 Berlin
Web: https://www.hotel-dahlem.de/
Getting to ZIB: 4 minutes by bus 101 plus 150 metres to walk OR 20 minutes to walk

Hotel Eckstein
Address: Schildhornstraße 72, 12163 Berlin
Web: https://www.hoteleckstein.de/
Getting to ZIB: 25 minutes to walk

Organizers

Timo Berthold, Ambros Gleixner, Thorsten Koch, and Milena Petkovic.

For any questions, please contact us at coaw@zib.de.

Previous Workshops

  • Berlin 2020
    The first virtual CO@Work was held from September 14 to 25, 2020, with recorded lectures by more than 30 distinguished speakers and interactive sessions organized for different time zones.
  • Berlin 2015
    From September 28 to October 10, 2015 more than 160 students from 29 countries, covering all continents except Antarctica, participated in the course held at Zuse Institute Berlin.
  • Berlin 2009
    From September 21 to October 9, 2009 many students from all over the world participated in the course held at the Zuse Institute Berlin.
  • Berlin 2005
    From October 4-15 more than 100 students out of 10 countries participated in the course held at the Zuse Institute Berlin.
  • Görlitz 2006
    From September 3-15 parts of the course where discussed during the Görlitz summer school of the German National Academic Foundation.
  • Beijing 2006 From September 25 to October 6 more than 40 students from all over China attended the course as part of the Workshop Optimization Methods and Applications at the Morningside Center of Mathematics, Chinese Academy of Sciences.