DYNAMO: Scalable and Data-Driven Algorithms for Optimization Problems in Dynamic Graph Streams

Research Project, 2025 – 2028

The assignment problem is a foundational optimization problem with applications across logistics, resource allocation, and, more recently, energy systems. Traditional solutions rely on the availability of sufficient memory to store and process all input data—nodes, edges, and weights. However, in today’s era of massive datasets, this assumption is no longer feasible. The semi-streaming model offers a promising solution, operating within memory constraints that scale linearly with the number of nodes while handling edge data dynamically as it arrives in a stream.

This PhD project aims to design innovative algorithms tailored to the semi-streaming model, with a focus on handling dynamic graph streams. The research will combine theoretical insights with practical applications to advance the scalability and efficiency of algorithms for assignment problems and other optimization problems in constrained environments.