Landing earlier or later than the specified time will cost each flight, and existing techniques do not measure time factors, so the cost of delay penalties is very high, while there are many techniques. In order to reduce this penalty, in this article, the ALP problem is investigated and then, with the help of an optimization function, a model to increase efficiency is presented. In general, the problem of sequencing tasks to determine the order of their execution on machines to reduce Or increase) is the criterion in question in optimizing the order of entry operations, both in regulations and in scientific journals. In the early stages of air traffic sequencing, feature-based inbound management and navigation are used to expand design horizons, enabling traffic surveillance in both take-off and landing modes. The aircraft landing sequence is centralized by examining parameters such as reducing apron and parking costs, minimizing latency and early arrival times, and minimizing fuel consumption costs. Finally, this paper intends to obtain a new way to improve the quality of scheduling programs and reduce their execution time by using theoretically validated algorithms and adapting them to the challenges of scheduling. Experimental experiments were performed on the data set of Mashhad Shahid Hasheminejad International Airport and showed that the main scheduling objectives can be better achieved with this method.