Multi objective Model of airport gate scheduling problem using NSGA-II algorithm and epsilon constraint

Gate scheduling is a key activity at airports that is proposed as an optimization problem. The main purpose of this problem is to find an assignment for the flights arriving and departing while satisfying a set of practical constraints. Studies show that the gate assignment tables have been used to minimize the gate flights delay and maximize the gate efficiency and productivity. Depending on the situation, different objectives become important. If the load balancing with number of passengers in the gates becomes a bottleneck one has to make sure that the flights are equally spread over the different gates. This load balancing objective function has to be balanced with other objectives, especially minimization total delay time and maximization of the total gate assignment preference score. The related problem is formulated as a mixed-integer programming (MIP). We address this problem using real life data from Mehrabad International Airport for both small and medium size problem. To find the set of Pareto solutions, NSGA-II algorithm is proposed to demonstrate the effectiveness of the solutions which is obtained in small dimensions compared with the results obtained by the method of epsilon constraint. The results show that the percentage of error of objective function compared to epsilon constraint method is less than 1.5% for all problems. Indeed, this shows the efficiency of proposed algorithm which is recommended for solving the medium and large size problem.