CORDIS - EU research results

Modeling and forecasting supply networks using functional time series and mathematical programming

Project description

Ensuring future supply meets demand: innovative modelling of large-scale supply networks

The efficient and effective distribution of goods and services requires planning. Decision-making depends on accurate predictions of supply and demand to ensure needs can be met. The considerations are complex, particularly for large-scale networks such as gas and water distribution. With the support of the Marie Skłodowska-Curie Actions programme, the NETOPT project will model and forecast large-scale network flows. The high-frequency forecasting model will analyse complex spatial and temporal dynamics using functional data analysis. The aim is to accommodate the high dimensionality of real-life Big Data and the time series generated by sampling random functions at regular time intervals. Mathematical programming will underlie the mathematical models designed to solve decision problems.


In NETOPT, we will develop an innovative high-frequency forecasting model that analyses complex spatial and temporal dynamics in large-scale networks under demand and supply constraints. Using supply networks as an example, NETOPT aims to model and forecast large-scale network flows using a Functional Time Series (TS) and Mathematical Programming (MP) approach. The network model proposed in NETOPT can optimize decision planning and efficient scheduling by reducing financial and technical risks in transmission and distribution networks, such as gas and water networks. To demonstrate the practical effectiveness of our new approach, we will implement models to describe and predict hourly gas flows for several days ahead in the German high-pressure gas transmission network using real-world data. Efficient prediction and interpretation of the complex dynamics in transport and distribution networks is a crucial component of an intelligent decision support system that helps to reach the climate targets of the European Green Deal in a fair, cost-effective, and competitive way.


Net EU contribution
€ 173 847,36
10623 Berlin

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Berlin Berlin Berlin
Activity type
Higher or Secondary Education Establishments
Total cost
No data