Regarding the large number of flights that a hub airport usually has to serve and the competitiveness in the aviation industry, optimal scheduling of limited and expensive airport resources such as gates is really vital. This work focuses on the efficient scheduling of airport gates to achieve a balance between three important goals, namely reducing the walking distance of passengers, decreasing the number of flights assigned to the gates different from their reference gates as well as widening the total shopping area passed by passengers while walking to, from or between the gates. A set of different scenarios is considered for the arrival of flights regarding the possible delays. Robust multi-objective optimisation is followed through an exact solution approach according to the weighted sum method by the Baron solver as well as a metaheuristic method consisting of the hybridisation of multi-objective particle swarm optimisation (MOPSO) and the multi-objective simulated annealing (MOSA). The sets of Pareto-optimal solutions obtained by these two methods along with those of the pure MOPSO, MOSA and a tabu search algorithm from the literature are compared based on some evaluation metrics and with the aid of a statistical test.