A New Intelligent Approach to Aircrafts Take-off/Landing Planning at Congested Single Runway Airports
Nowadays, air transportation has gained a significant growth due to its advantages in transporting goods and passengers. The rapid growth of this activity and some limitations in different parts of aviation operation often cause traffic congestion the mismanagement and proper planning of which can lead to a lot of flight delays; accompanied by different problems. In order to appropriately systematize air traffic congestion various researches have been done during the recent two decades the major part of which is dealing with planning of aircrafts taking-off and landing. Thus, in the current study; and for the first time, the two algorithms Biogeography-Based Optimization (BBO) and Particle Swarm Optimization with Constriction Coefficient (CPSO) deal with a feasible planning of aircrafts take-off /landing, taking modern conditions and limitations into account. Simulations prove that adding rich and effective knowledge to optimization process can, to a large extent, undue and redundant outcomes; and increase convergence rate of the above algorithms. This can be followed by over 50% of total flight delays compared with First-Come/First-Serve (FCFS) plan. Besides, comparing the results of applying the two new optimization algorithms showed that BBO can be more effective than CPSO because of its better research domain.
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