Keywords: Predictive optimization; bike-sharing; inventory management; demand forecasting
Team participants: Daniele Gammelli; Filipe Rodrigues; Francisco C. Pereira
Lead Organization: DTU – Technical University of Denmark
In this interdisciplinary project, we follow an integrated approach and build on concepts from data-driven optimization, stochastic programming, and machine learning to develop decision support with the application to transportation and mobility, in particular for bike- and car-sharing. Based on bike- and car-sharing data from the cities of Copenhagen and Munich, exploration and exploitation methods and active learning concepts will be developed to support strategic and operational decision-making with regard to capacity, inventory positioning, and resource rebalancing under uncertainty in large systems with distributed (competitive) decision making. This integrated approach requires knowledge from the disciplines of transportation and management as well as from stochastic optimization and machine learning.
- DTU – Technical University of Denmark
- Technical University of Munich – Chair of Logistics
Eurotech Ph.D. alliance