The building stock accounts for roughly 36% of the EU’s greenhouse gas emissions, and it is estimated that 85-95% of current buildings will still exist in 2050. The importance thus falls on improving the energy efficiency of the existing stock to meet future emission targets. Retrofitting is fundamental to improving the efficiency of existing buildings, however the associated decision-making process is subject to many conflicting criteria including those which are energy-related, environmental, social, financial, and so forth. This problem is exacerbated at the stock-level where any attempt at planning raises questions around how to treat the specifics of each stock, the allocation of limited resources, and which retrofits to consider. Furthermore, there is a lack of developed methods to assist with this. Retrofit optimisation tools have been developed and applied to individual buildings; however there are very few studies which perform stock-level optimisation. This research therefore aims to develop a methodology which allows multi-objective optimisation to be performed over a segment of the stock. In doing so, it aims to expose the associated challenges, explore the extra complexity faced at this scale, and improve the feasibility of stock-level optimisation. This kind of approach would be well suited to scenarios where there is a constraint on budget/resources, which is often the case in real-world scenarios. Such a methodology could be valuable to local authorities, many of which are currently in the process of determining the best strategies to decarbonise their building stock.