Digital Twins for City Logistics

Due to the complexity of modern supply chains, it is difficult to predict what the effect will be of a decision aimed at reducing greenhouse gas emissions, such as choosing the location of a pick-up point, or changing the travel route for a vehicle. Digital twins make it possible to try these decisions in a virtual environment before applying them in real life. This helps policymakers in governments and companies gain a better understanding of the consequences of a decision, which reduces the risks and uncertainties of the radical new decisions that are necessary to achieve the sustainable supply chain of the future. With the rise of digital twins for smart cities, such as the Atlas Livable City developed by the Logistics Community Brabant, more data is readily available than ever before. Yet most existing optimization techniques, which are necessary for minimizing an objective such as travel time or greenhouse gas emissions, are not able to deal with such complex virtual environments. Data-driven optimization techniques are therefore an active area of research. Examples of this are optimization heuristics learned with machine learning, and surrogate models for optimization. This project will contribute to this active research landscape by making data-driven optimization techniques that are suitable for digital twins. The main application is the reduction of greenhouse gas emissions in last-mile delivery by choosing the locations of pick-up points in urban environments.

May 2022 – Paper Joint Inventory and Fulfilment Optimization for an Omnichannel Retailer: A Stochastic Optimization Approach. 

November 2022 – BNAIC/BeNeLearn (AI & ML conference for Belgium, Netherlands & Luxembourg). We survey Digital Twin (DT) applications in Urban Logistics (UL) to provide a solid characterization of an ULDT and lay the foundations of integrating it in an Artificial Intelligence framework. Poster presented at BNAIC.
Among the contributors to the idea behind this publication was Joost de Kruijf whose proposal of what such a DT may look like through Atlas Leefbare Stad (a virtual model of cities in the Netherlands) helped in formulating our discussion. BNAIC: https://lnkd.in/eAtH-Q93, Atlas: https://lnkd.in/exf_V_j7

June 2023 – Annual AI Planner of the Future Event. Presentation. 

June 2023 – Publication Digital twin applications in urban logistics: an overview in Urban, Planning and Transport Research – Volume 11, 2023 – Issue 1 

August 2024 – Paper characterization of urban logistics digital twins published a year ago. Developing method for optimizing large scale VRP using machine learning. Submission expected in summer. Company hosted an event stressed the added value of the findings to the students. Conducted an interview as part of communication team AIPoF demonstrate relevance of their work to research. 

Abdo AbouelrousYingqian Zhang Laurens Bliek 

More info: escf@tue.nl