Mathematical Model of Optimal Assignment of Aircraft to Apron Gates with Safety Constraint Considerations

Airports are one of the most vital infrastructures of any country, which play an important role in transporting cargo and passengers to different parts of the world. The preservation and optimal use of airport resources and assets is one of the main goals of airport managers. On the other hand, airlines have a special concern on saving time, fuel consumption, maintaining passenger satisfaction, and so on. One of the most important resources in the world's major airports are the gates of the passenger terminals of airports, which have an undeniable aspect in the better performance of the airport. The assigning of aircraft to these gates has long been a concern for researchers in operations research as well as air transport activists. This research deals with the issue of assigning aircraft to the passenger terminal gate. The problem of optimal gate assignment is a complex issue and requires consideration of many parameters and variables in order to achieve the desired result. In this research, it’s tried to solve the gate allocation problem by presenting a suitable model. Providing an appropriate linear model is one of the main challenges of the problem. A special attention has been paid to the issue of safety. Therefore, by applying safety restrictions, a suitable model is provided. The main purpose of this study is to minimize the scatter of idle (lost) gates while not preventing mismatch between flight size and gate and also justifying safety needs. These cases are assigned and examined in the framework of the optimization model in this research. To solve such problems, which are usually not possible by manual calculations or are very time consuming, the metaheuristic algorithms are used. Since because NP-Hard nature of problem, it is very time consuming and difficult in the usual way. Therefore, this study tries to provide an efficient and fast way to solve the gate assignment problem. In the proposed method, first all the sentences of the objective function were considered as, then all were divided into two categories of hard and soft constraints. On the other hand, in the model of the basic method, the power of two terms in the objective function is used. The proposed model was modified. In the end, it was tried to modify the terms of the objective function and constraints in such a way that in addition to meeting the expectations and constraints of the problem, it allows the use of two flights from the same gate (MARS effect) to increase resource efficiency. The method is based on a genetic algorithm that includes the initial population, selection, combination or mutation, generation of a new offspring, and re-selection. In this study, 5 scenarios with various flights and gates have been used. The improvement of total idle times in the first scenario was 72.75%, in the second scenario 76.92%, in the third scenario 82.38%, in the fourth scenario 82.38% and in the fifth scenario 79.67%. All of results. Show the efficiency of proposed model.