This seminar presents recent research on classical and quantum optimisation methods for strategic decisions in manufacturing supply chains. We discuss mixed-integer programming models addressing supplier selection, facility location, and line balancing, highlighting their effectiveness in managing real-world constraints. The mathematical models are solved using advanced tools, including
branch-and-cut algorithms, simulation techniques, and quantum computing approaches. Applied to realistic scenarios, these models provide valuable insights into solution quality and computational performance. We then introduce Quadratic Unconstrained Binary Optimization (QUBO) as a flexible framework for reformulating supply
chain problems to suit quantum computing paradigms. Special attention is given to QUBO formulations for facility location and load balancing, solved using both quantum annealers and the Quantum Approximate Optimization Algorithm (QAOA) on gate-based quantum systems. The
seminar compares classical and quantum approaches, highlights their respective advantages and limitations, and discusses hybrid modelling strategies that integrate both technologies. This talk is intended for postgraduate students and researchers interested in operations research,
quantum computing, and supply chain optimisation.