To reduce the CO2 emissions of the maritime industry, several alternative fuels are being researched to possibly achieve this goal. The absence of an infrastructure for alternative fuels in the current port environment is one of the barriers towards implementation of these high potential fuels. The goal of this thesis project was to create an optimization model which can provide more insight into the initial sizing, phased growth and corresponding cost of an infrastructure needed for maritime transport using different forms of alternative fuels. The corresponding main research question is: "How do the port refueling infrastructures of sodium borohydrate, liquid hydrogen and gaseous hydrogen compare to each other with respect to costs and supply chain set-up in terms of where, when, and at what sizes to build up the production, storage, distribution and refueling facilities?" To answer this research question a single-objective multi-period mathematical optimisation model (Mixed Integer Programming) has been created for the port refueling environment. The most important model innovations are the inclusion of a maritime refueling convention and the possibility to model less conventional alternative fuels such as sodium borohydrate (NaBH4). Furthermore, input for the model has been gathered from several sources. Next, some parameters of the model have been varied to research their effect on the total alternative fuel infrastructure. As a result it has been found that the gaseous hydrogen infrastructure is the cheapest with respect to facility capital costs and facility operating costs, but was the most expensive when looking at transportation of the fuel within the port. The liquefied hydrogen was the cheapest with respect to fuel transportation, but scored average on facility capital cost. Furthermore it is the most expensive infrastructure with respect to facility operating cost. The NaBH4-infrastructure is the most expensive infrastructure when looking at the facility capital cost, but scores average on facility operating cost and transportation cost. Overall the gaseous hydrogen infrastructure was the cheapest infrastructure, followed by liquefied hydrogen. The NaBH4-infrastructure turned out to be the most expensive with the current input. The input parameters for NaBH4 are still very uncertain at this stage as the production of this fuel on a large scale is still at a low Technology Readiness Level and there is still unfamiliarity with large scale storage and transport of the substance. A reduction in the corresponding cost parameters would lead to the NaBH4-infrastructure becoming more competitive with a liquefied hydrogen infrastructure. The input used in the model should thus be further researched to reduce the corresponding uncertainties. While the current model focuses on optimising the infrastructure from a cost perspective, it must be taken into account that other factors also influence the favouring of certain alternative fuels, such as safety, policy, public acceptance and the preference for certain fuels from the perspective of the maritime users. In future research the expansion of the model towards a multi-objective model should be evaluated.