AOO2022: 09 May 2022 - Programme & Abstracts

When: Monday, 09 May 2022, 09:00-17:00.

Where: Industriens Hus, H. C. Andersens Blvd. 18, 1553 København, Denmark.

Register here


After two chaotic Covid-19 years, our annual conference on applied mathematical optimization is back to the regular spring schedule! AOO 2022 takes place on Monday, 09 May 2022 at Industriens Hus in Copenhagen (09:00-17:00).


Below you find the programme, followed by the abstracts of the conference talks.

 

Programme


The workshop program includes five talks from OR experts and practitioners, and there will be ample time for networking:

09:00-10.00 Registration and refreshments 10:00-10:10 Welcome + Announcements 10:10-10:55 Anita Schöbel, Head of Fraunhofer Institute for Industrial Mathematics

Robust optimization for real-world applications 11:00-11:45 Simon Bull, Digital Expert at McKinsey & Company

Supply Chain Optimization - Applications in Industry 11:45-12:00 Sponsor pitches 12:00-13:00 Lunch 13:00-13:45 Vladimir Fux, Data Science Lead at Zalando

Pricing at scale: operations research in e-commerce 13:50-14:35 Pierre Pinson, Professor of Operations Research, DTU Management

Monetizing data and information in analytics tasks 14:35-14:50 Sponsor pitches 14:50-15:15 Coffee break 15:15-16:00 Janus Asmussen, Lead Data Scientist, and Mathias Als, Data Scientist at Ecco

Intelligent Replenishment of the ECCO retail networks 16:00-16:05 Closing

 

Speakers and Abstracts


Anita Schöbel, Head of Fraunhofer Institute for Industrial Mathematics Title: Robust optimization for real-world applications Abstract: Most real-world optimization problems contain parameters which are not known at the time a decision is to be made. In robust optimization one specifies the uncertainty in a scenario set and tries to hedge against the worst case. Classical robust optimization aims at finding a solution which is best in the worst-case scenario. It is a well-studied concept but it is known to be very conservative: A robust solution comes with a high price in its nominal objective function value. This motivated researchers to introduce less conservative robustness concepts iin the last decade. Moreover, many real-world problems involve not only one, but multiple criteria. While robust single-objective optimization has been investigated for 25 years, robust multi-objective optimization is a new field in which already the definition of "robust" is a challenge. In the talk, several robustness concepts will be discussed and illustrated at real-world applications which are currently tackled at Fraunhofer ITWM. Simon Bull, Digital Expert at McKinsey & Company Title: Supply Chain Optimization - Applications in Industry Abstract: In recent years, supply chains have become more complex and more challenging to operate effectively. Growing product portfolios result in longer, more interlinked supply chains, and recent global events have driven up volatility and uncertainly, highlighting needs for robust, flexible, and responsive planning capabilities. Additionally, companies' growing awareness and concern for their environmental footprint necessitates planning in holistic, transparent manner with clear targets and objectives. These challenges can be addressed by optimisation and OR-driven decision support tools. Integrated, end-to-end tooling that is able to produce feasible plans over multiple time-horizons can address the challenge of growing complexity while bringing responsiveness, flexibility, and holistic transparency.

I will explore some of the trends we see in the application of optimisation to supply chains, some common themes across industries, and will deep-dive on a specific case of developing a new optimisation-driven approach for supply chain planning. Vladimir Fux, Data Science Lead, Zalando Title: Pricing at scale: operations research in e-commerce Abstract: How to recommend discounts for hundreds of thousands of articles, when your model does not fit in a exact solver? How can decomposition methods be applied in practice and constitute a reliable product? We will talk about Operations Research problems becoming engineering challenges and Machine Learning tools helping out in the context of Zalando, the largest European fashion platform.

Pierre Pinson, Professor of Operations Research, DTU Management Title: Monetizing data and information in analytics tasks Abstract: Data is becoming one of the most valuable commodities, though our current views on data sharing and governance are quite black and white (open data or no sharing). It makes sense however to think of how to monetize data through various forms of markets. In practice the value of data is revealed through analytics tasks, e.g. optimization and forecasting problems. We will zoom into specific proposals for the monetization of data and information, also with some energy-related examples.

Janus Asmussen, Lead Data Scientist & Matthias Als, Data Scientist, ECCO

Title: Intelligent Replenishment of the ECCO retail networks

Abstract: ECCO has started many new initiatives to enable the business to rely on automated and data-driven decision making. The retail network is still a core part of the ECCO customer experience giving rise to many inventory management optimization problems. One such problem lies in automatic replenishment of stores to eliminate manual processes while maximizing the profit of the retail network as a whole. We will present an overview of the replenishment optimization problem, its results in ECCO, and our setup that allows for automated decision making.


 

AOO 2022 is sponsored by Gurobi, Mosek, Ørsted, and Sealytix!



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