Strategic Asset Management Optimisation

Project dates: 01/01/2019 - Ongoing

Long-term asset management and maintenance planning is a complex task. Decisions include when to perform maintenance, when to upgrade an asset, and how much to spend. These decisions become even more complex when considering asset dependencies and networks. Asset management software typically uses bespoke algorithms to produce maintenance schedules.

In this project, we formulate the asset management problem using a Mixed Integer Programming (MIP) approach. We aim to use metaheuristic approaches including Ant Colony Optimisation and Genetic Algorithms to provide good solutions in short amounts of time. By using a MIP approach we are able to incorporate complex dependencies and policy with simple constraints.


Chief Investigators

Team

Other Team Members

Andrew Haselgrove (student)

Partners