In this paper, we introduce the Air Freight Flight Schedule Development Problem (AFFSDP). In this problem, a cargo-only carrier has to adjust an existing flight schedule based on changes in the predicted demand. The result of this research is a model that combines airport selection, fleet routing and cargo routing, together with the use of a (random) mandatory flight list and timetable setting for all other optional flights. The model is formulated as a Mixed Integer Linear Program (MILP). To reduce the pre-processing time of the model two meta-heuristics have been implemented that reduced the run time from several hours to minutes. To improve the performance of the model, all fractional numbers have been reshaped to integer numbers. The symmetry of the model was brought to a minimum by implementing a path-preference model. The model was tested with 3 aircraft types, for 3 different demand scenarios and 3 different freedoms. This sums up to 27 unique test cases. Overall, the results show that against a benchmark solution the total serviced demand could be increased by 20-50%.