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군용 헬리콥터 조종사 스케줄링 모형

A Model of Military Helicopter Pilot Scheduling

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참고문헌

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주제분류산업공학

초록

In this paper, we introduce a pilot's scheduling model which is able to maintain and balance their capabilities for each relevant skill level in military helicopter squadron. Flight scheduler has to consider many factors related pilot's flight information and spends a lot of times and efforts for flight planning without scientific process depending on his/her own capability and experience. This model reflected overall characteristics that include pilot's progression by basis monthly and cumulative flight hours, operational recent flight data and quickly find out a pinpoint areas of concern with respect to their mission subjects etc. There also include essential several constraints, such as personnel qualifications, and Army helicopter training policy’s constraints such as regulations and guidelines. We presented binary Integer Programming (IP) mathematical formulation for optimization and demonstrated its effectiveness by comparisons of real schedule versus model's solution to several cases experimental scenarios and greedy random simulation model. The model made the schedule in less than 30 minutes, including the data preprocessing process, and the results of the allocation were more equal than the actual one. This makes it possible to reduce the workload of the scheduler and effectively manages the pilot's skills. We expect to set up and improve better flight planning and combat readiness in Korea Army aviation.

Abstract

In this paper, we introduce a pilot's scheduling model which is able to maintain and balance their capabilities for each relevant skill level in military helicopter squadron. Flight scheduler has to consider many factors related pilot's flight information and spends a lot of times and efforts for flight planning without scientific process depending on his/her own capability and experience. This model reflected overall characteristics that include pilot's progression by basis monthly and cumulative flight hours, operational recent flight data and quickly find out a pinpoint areas of concern with respect to their mission subjects etc. There also include essential several constraints, such as personnel qualifications, and Army helicopter training policy’s constraints such as regulations and guidelines. We presented binary Integer Programming (IP) mathematical formulation for optimization and demonstrated its effectiveness by comparisons of real schedule versus model's solution to several cases experimental scenarios and greedy random simulation model. The model made the schedule in less than 30 minutes, including the data preprocessing process, and the results of the allocation were more equal than the actual one. This makes it possible to reduce the workload of the scheduler and effectively manages the pilot's skills. We expect to set up and improve better flight planning and combat readiness in Korea Army aviation.

참고문헌 (12)

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  2. Hohzaki, R., "Flight Scheduling for the SH-60J Military Helicopter", Military Operations Research, 16(2), pp.5~17 (2011)
  3. 이재용, "국내 주요 산업별 스케줄링 기법의 연구동향", 한국산업경영시스템학회지, 41(1), pp.59~69 (2018), 한국산업경영시스템학회[DOI]
  4. 이문걸, "전투비행대대 비행스케줄링에 관한 연구", 한국경영과학회지, 39(2), pp.37~48 (2014), 한국경영과학회[DOI]
  5. 이문걸, "복좌 전투기 조종사 스케줄링 모형", 대한산업공학회지, 46(3), pp.256~268 (2020), 대한산업공학회[DOI]
  6. Lee, Y. I., "A Study on the Daily Squadron Crew Scheduling", Journal of the Military Operations Research Soci-ety of Korea, 15(1), pp.28~43 (1989)
  7. ROKA, "Air Operations and Safety Management Regulations", Republic of Korea ARMY, ~ (2019)
  8. ROKA, "Army Aviation Operations Command Admini- strative Rules", Republic of Korea ARMY, ~ (2019)
  9. Rusdiansyah, A., "A Hybrid Scatter Search Heuristic for Solving Cockpit Crew Rostering", Journal Teknik Industri, 20(2), pp.141~152 (2018)
  10. Shohoni, M. G., "Delta Optimizes Continuing-Qualification-Training Schedules for Pilots", INFORMS, 33(5), pp.57~70 (2003)
  11. Stojkovic, M., "An Optimization Model for the Simultaneous Operational Flight and Pilot Sche-duling Problem", Management Science, 47(9), pp.1290~1305 (2001)
  12. Wilensky, U, "An Introduction to AgentBased Modeling : Modeling Natural, Social, and Engi- neered Complex Systems with NetLogo" (2015), MIT Press

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