As part of the OPTIMA international student exchange, I undertook a four-week research exchange at Lancaster University in England, from May 9th to June 9th, 2025. The exchange was hosted by the STOR-i Centre for Doctoral Training, one of the world’s leading research centres in statistics and operational research. This exchange proved to be a highly rewarding experience, offering valuable opportunities for academic development, collaboration, and professional growth.

The primary goal of this exchange was to develop my existing model and methods to incorporate product substitution, a key operational challenge in retail inventory networks, particularly under conditions of uncertainty and stockouts. Another important objective was to build connections and foster future collaborations with leading academics in this field. In addition, the exchange provided an invaluable opportunity to work within the STOR-i research environment, encouraging discussions around projects, methods, and shared challenges.

I chose to carry out this work at Lancaster University to collaborate with Dr. Anna-Lena Sachs, a leading academic in inventory optimisation and machine learning, whose expertise closely aligns with the focus of my PhD: optimising inventory replenishment and fulfilment in omnichannel retail environments- reinforcement learning-based algorithms.

In collaboration with Dr. Sachs, we developed a comprehensive modelling and algorithmic framework that integrates substitution probabilities into the inventory optimisation process. This framework is designed to generate practical insights for decision-makers, enabling more effective management of product availability by incorporating customer substitution behaviour into optimisation models. The resulting methodological advancements enhance both the theoretical robustness and practical relevance of the inventory management problem and constitute a significant contribution to the academic literature on omnichannel supply chain optimisation.

The visit began with a seminar presentation, where I introduced my ongoing PhD research, shared the goals of the exchange, and introduced the planned work with Dr. Sachs. This sparked insightful conversations, particularly with academics also working on the same topic.

Being based in the main STOR-i office enabled daily interaction with students and academics. This collaborative environment fostered knowledge sharing and idea exchange that enriched my understanding of applied methods across various projects. I also participated in four PhD student forums, including detailed discussions on Markov chains and machine learning techniques, which broadened my perspective and introduced me to a variety of modelling approaches used by STOR-i researchers in the field.

On the final day of the visit, I delivered a presentation to the STOR-i community summarising the key outcomes of our collaboration. This included the formulation of a product substitution model, initial results, and a roadmap for integrating this framework into the larger structure of my PhD thesis. This session opened up conversations around future research directions and potential collaboration.

I sincerely appreciate OPTIMA’s support in facilitating this international collaboration, which not only enriched my academic network and laid the foundation for future collaborations, but also supported the development of my methodological approaches—bringing my research closer to practical application and strengthening its contribution to the academic literature.