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## A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules

#### Hamit Taner UNAL [1] , Fatih BASCIFTCI [2]

##### 17 30

Today, Air Force is the most effective element in defense and military organizations of the countries. In parallel with the technological developments in the defense industry, military combat aircraft and other air support elements contribute significantly to the success of the operations. The training of flying personnel using advanced technology and high capability weapons and equipment is getting more and more important every day. Individuals, who fly on high-cost platforms such as combat pilots and AWACS controllers are required to go through long and intensive training in order to achieve combat-ready status.        Given the high costs of actual flights for training, a rigorous planning and scheduling activity is carried out to ensure that resources are used effectively and expenditures are minimized. In this paper, genetic algorithms were utilized for integrating AWACS flight training programs into crew schedules. The criteria which affect the scheduling were mathematically modeled and fitness function of the existing AWACS Crew Scheduling algorithm was revised. In order to measure the performance of the designed model, crew scheduling was carried out through a notional flight schedule of an artificial AWACS squadron similar to real-world examples. Genetic algorithms have been applied through a novel software developed as a test bed. As a result of the experiements, the algorithm was able to schedule all individuals based on the relevant criteria outlined in the guidelines, assigning students to flights with correct student-intructor pairings and complying with priorities selected by user while reaching the optimum solution in a reasonable time.

AWACS, Crew scheduling, Genetic algorithms, Air force, Optimization, Flight training programs
 Bibtex @araştırma makalesi { epstem492298, journal = {The Eurasia Proceedings of Science, Technology, Engineering \& Mathematics}, issn = {}, eissn = {2602-3199}, address = {ISRES Publishing}, year = {2018}, volume = {4}, pages = {28 - 34}, doi = {}, title = {A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules}, key = {cite}, author = {UNAL, Hamit Taner and BASCIFTCI, Fatih} } APA UNAL, H , BASCIFTCI, F . (2018). A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics, 4 (), 28-34. Retrieved from http://dergipark.gov.tr/epstem/issue/40805/492298 MLA UNAL, H , BASCIFTCI, F . "A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules". The Eurasia Proceedings of Science, Technology, Engineering & Mathematics 4 (2018): 28-34 Chicago UNAL, H , BASCIFTCI, F . "A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules". The Eurasia Proceedings of Science, Technology, Engineering & Mathematics 4 (2018): 28-34 RIS TY - JOUR T1 - A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules AU - Hamit Taner UNAL , Fatih BASCIFTCI Y1 - 2018 PY - 2018 N1 - DO - T2 - The Eurasia Proceedings of Science, Technology, Engineering & Mathematics JF - Journal JO - JOR SP - 28 EP - 34 VL - 4 IS - SN - -2602-3199 M3 - UR - Y2 - 2019 ER - EndNote %0 The Eurasia Proceedings of Science, Technology, Engineering & Mathematics A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules %A Hamit Taner UNAL , Fatih BASCIFTCI %T A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules %D 2018 %J The Eurasia Proceedings of Science, Technology, Engineering & Mathematics %P -2602-3199 %V 4 %N %R %U ISNAD UNAL, Hamit Taner , BASCIFTCI, Fatih . "A Genetic Algorithm Approach For Integrating Awacs Flight Training Programs Into Crew Schedules". The Eurasia Proceedings of Science, Technology, Engineering & Mathematics 4 / (Aralık 2018): 28-34.