Aviation emissions present a significant contribution to climate change. The rate at which new technology is developed cannot suffice the emission reduction requirements for the growth of this industry. Therefore, new areas of improvement, such as operational changes, should be considered. The inclusion of stop-overs in long-haul routes can potentially result in a reduction of the fuel required for certain routes. This strategy is known as intermediate stop operations (ISO) and in order to test its performance, it is necessary to study economic, environmental and operational consequences. The implications of ISO are best represented with the model of an airline network. The simulation within which ISO is tested is built using a dynamic programming approach to obtain an optimal fleet assignment and network schedule. Dynamic programming allows for a division of the optimization problem into smaller subroutines, which significantly reduces computational time. Moreover, this approach allows solving the optimization problem such that the level of the activity of the airline is not directly proportional to the outcome. The case study under which the proposed methodology is tested belongs to the weekly operations of the airline Alitalia. Long haul operations are evaluated for the base scenario which imitates current operations and then compared to the introduction of a stop-over. Splitting flights into two legs results in a reduction of the fuel consumption per passenger transported of around 5% and a subsequent reduction in climate impact of 0.1%. These values are achieved compromising total flight time, however, no reduction in the profit generated per passenger is observed.