Enhancing and expanding public transportation is becoming a crucial solution to the high costs of congestion and the escalating environmental impacts of car-centric transportation systems observed in numerous cities today. One approach to enhance the quality of public transportation, and thereby boosting its ridership, is through the intelligent design of stop locations. Strategically locating stops can increase coverage of transit and reduce overall trip times. However, selecting stop locations is a relatively intricate task as it involves striking a balance between two competing objectives; accessibility and efficiency. In this thesis, a multi-objective optimisation model is presented to make the trade-offs between several factors influencing stop locations explicit. The model enables a comprehensive assessment of transit objectives by evaluating alternatives, determining demand and running times in detail, and examining network effects. Relevant factors such as sociodemographic characteristics within catchment areas, travel patterns, transit alignments, and transfer locations are modelled for different areas of the system. The developed model is employed in a case study that focuses on the tram network of The Hague in the Netherlands. Various objectives are evaluated to determine the optimal stop locations and the factors that affect them. The results reveal that the ideal stop locations are contingent on the objectives established. Despite this, the number of stops in the system of The Hague is reduced by at least 6% for all considered objectives. When the user costs are minimised, an increase in ridership of 4% can be achieved, whilst saving 3% of operator costs. Moreover, it is concluded that optimising the network for either the operator or society results in 17% fewer stops, and a subsequent estimated cost saving of 9%, without any negative impact on ridership.