Optimizing the Airline Routing Cost using Linear Programming and PSO Algorithm

The transportation industry of any country represents the economic situation and the level of industrial development of that country, so this industry should be considered as one of the most essential factors in any society's economic, cultural, and social development. Exact planning and scheduling in airline transportation is inevitable. The crew scheduling problem is defined as creating a set of tasks to provide daily transportation services by creating a set of trips and assigning crews to them at minimum cost. So far, many studies have been carried out in this field, and researchers have presented several methods and algorithms to solve this problem. This research assumes that the air fleet consists of different types of planes, which are classified into different types based on their capacity and operating cost. The time it takes for a plane to travel back and forth depends on the type of plane and the length of the round trip. However, there may be no flights due to the proximity of the distance or low passenger demand. The main goal of this research is to determine the best flight schedule for the country's airlines using the linear planning method to minimize the total cost of transportation and passenger movement. Due to the non-linearity of the proposed model, a meta-heuristic method has also been developed based on the particle swarm optimization approach and simulated in MATLAB on sample problems in small, medium, and large dimensions. The calculation results indicate the efficiency and stability of the proposed method.