In the coming decades, offshore renewable energy is expected to play a crucial role in the decarbonisation of global electricity supply essential for limiting anthropogenic greenhouse gas emissions to an acceptable level. The cost of utilising expensive vessels to install and maintain these marine energy devices represents a significant proportion of their life-cycle cost and one of the major barriers to their continued development. It is vitally important to estimate accurately these costs and attempt to reduce them as much as possible. This thesis investigates the use of time-domain simulations of marine operations to estimate the likely duration and manage the inherent risks of an offshore project. The development and application of an original time-domain simulation software are described through a case study that supported construction of a Round 3 offshore wind farm. Analysis completed in advance of the project identified the most suitable installation strategy with a potential reduction in indicative cost of up to $6m. Simulations performed during the project enabled the early identification of significant deviations from initial estimates; such as the mean observed duration of a critical activity midway through the project being approximately 30% lower than initially specified, eventually leading to a 10.8% reduction in the estimated project duration. Detailed analysis of the operational data after project completion identified the importance of the learning phenomenon associated with repetitions of identical operations and the accurate representation of random delays and stoppages. Implementing the learning factor had the effect of reducing mean project duration by 10%, while accounting for technical downtime increased this estimate by 15%. The thesis shows that time-domain simulations are well-suited to the development of optimal strategies for the execution of marine operations and the subsequent minimisation of the duration and cost of offshore projects.