Shipping currently accounts for 2.89% of total global carbon dioxide emissions, although this could rise to 17% by 2050 if the shipping industry is left unregulated. Therefore, it is paramount that policy makers introduce regulations to reduce the emissions of shipping fleets. This is outlined by the International Maritime Organisation, which has produced a target of reducing the total carbon emissions of international shipping by 50% by 2050. One of the ways this can be achieved is by introducing carbon pricing measures, which will penalise fleets for the carbon they emit. This is done using measures such as emissions trading schemes or by placing a price per ton of carbon dioxide emitted. However, policy makers need to be mindful of the potential implications of these tax measures, such as fleets only operating in countries with little or no carbon pricing measures.

We want to identify what carbon measures achieve the aim of reducing carbon emissions from a fleet of vessels. For this, we need to simulate the routes vessels take whilst fulfilling orders, such that we can calculate the vessels' profits and carbon emissions. We will model the problem of assigning trades to vessels and constructing routes using agent-based simulations, allowing us to identify the profit and carbon emissions of the vessels. Moreover, the role of uncertainty within the real world will be accounted for, such as by modelling for weather and uncertain demand. We will then be able to simulate and compare different carbon pricing measures, so we can identify regulations which achieve a reduction of carbon emissions whilst ensuring the profitability of shipping companies. This simulation can further be used to investigate how implementing carbon measures alters the fleet composition of the vessels, such as the vessels' size and what type of fuel they use. Overall, this project will contribute to a deeper understanding of the optimal regulations needed to reduce the greenhouse gas emissions for a fleet of shipping vessels.