A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules
Today, Air Force is the most effective element indefense and military organizations of the countries. In parallel with thetechnological developments in the defense industry, military combat aircraftand other air support elements contribute significantly to the success of theoperations. The training of flying personnel using advanced technology and highcapability weapons and equipment is getting more and more important every day.Individuals, who fly on high-cost platforms such as combat pilots and AWACScontrollers are required to go through long and intensive training in order toachieve combat-ready status. Giventhe high costs of actual flights for training, a rigorous planning andscheduling activity is carried out to ensure that resources are usedeffectively and expenditures are minimized. In this paper, genetic algorithmswere utilized for integrating AWACS flight training programs into crewschedules. The criteria which affect the scheduling were mathematically modeledand fitness function of the existing AWACS Crew Scheduling algorithm wasrevised. In order to measure the performance of the designed model, crewscheduling was carried out through a notional flight schedule of an artificialAWACS squadron similar to real-world examples. Genetic algorithms have beenapplied through a novel software developed as a test bed. As a result of theexperiements, the algorithm was able to schedule all individuals based on therelevant criteria outlined in the guidelines, assigning students to flightswith correct student-intructor pairings and complying with priorities selectedby user while reaching the optimum solution in a reasonable time.
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