# Multi-Objective Gate Allocation Problem Based on Multi-Commodity Network Flow Model
## 2 Literature Review  
The gate allocation will significantly affect the quality of passenger service. Departing passengers want the distance from the waiting port to boarding the plane to be as short as possible and arriving passengers want the travel time from the aircraft to baggage claim to be as fast as possible. Transfer passengers want the distance between the corresponding two flight gates to be as short as possible. Since 1971, some scholars have paid attention to the problem of gate allocation considering passenger satisfaction [9], which is also the first group of people to pay attention to and solve the gate allocation problem. Among the optimization objectives from the perspective of passenger satisfaction, the most frequently used one is to minimize the walking distance of passengers. In earlier studies, most scholars only considered the single objective optimization problem [10; 11; 12; 13]. In the 21 st century, multi-objective optimization methods occupied the main proportion [14; 15; 16; 17; 18]. In addition, some studies changed the perspective of the optimization objective, such as minimizing the total waiting time of passengers [14] or minimizing the transit time of passengers [19; 20]. [PERSON] et al. [21] considered the transit time of passengers and the transit walking distance. Since overall passenger satisfaction is proportional to the number of passengers, the number of passengers is also considered an essential parameter of passenger satisfaction [22; 23] to reduce the overall walking cost of passengers and the possibility of missing flights as much as possible. Since 2000, scholars have begun considering the interests of airlines and airport operations more comprehensively. The continuous airport operation needs to ensure the satisfaction of passengers and airlines' preferences simultaneously to ensure the efficient operation and constant income of the airport. The primary consideration of the airport is to maximize the function of surface resources so that the utilization of resources can reach the optimal mode as close as possible. [PERSON] et al. [16] considered different airlines' preferences for gates and established a multi-objective model. [PERSON] [24] improved the utilization of gates by reducing idle time. It used a genetic algorithm to solve the problem. [PERSON] [25] also considered the utilization of gates and solved it using an adaptive particle swarm algorithm. In addition, the robustness of the gate is also regarded as an important perspective. For the possibility of changes in the arrival and departure times of flights, the dynamic ability of the optimization model can be improved by minimizing the variance of idle time [17; 26; 27]. Maximizing compatibility is also an option to enhance the robustness of gates [23; 28]. For airlines, ground operations must be performed as efficiently as possible with limited resources. Reducing the number of aircraft with unassigned gates [15; 17; 23; 28; 29; 30] and the number of aircraft allocated to remote gates [18; 31] can improve ground operation efficiency and reduce ground consumption costs. When the aircraft cannot temporarily reach the contact gate for various reasons, passengers must take airport buses to the location without the corridor bridge to board the plane, which consumes a lot of time and cost on the ground and reduces passengers' patience and comfort. In addition, reducing the total cost of towing an aircraft from a remote gate is also a method chosen by many types of literature. Using special airport vehicles such as tractors to tow aircraft requires considerable cost, so we try our best to avoid the arrival and departure flights of the same aircraft not being at the same gate and the situation that the aircraft needs to be towed to the corresponding gate. Towing operations can be reduced by minimizing the number of towing tasks [32; 33; 34] or the towing cost. [PERSON] and [PERSON] [35] developed a linear programming model to optimize the towing cost of aircraft under certain constraints.