Optimizing an F-16 Squadron Weekly Pilot Schedule for the Turkish Air Force

Abstract

Fighter squadrons in the Turkish Air Force fly according to weekly flight schedules. This scheduling requires a great deal of time, and the process is not optimal, as the Turkish Air Force doesn't have an automated tool for flight scheduling. There are many constraints to this scheduling, including crew rest, the number of sorties a pilot is required to fly in a month, and currency limits. In fighter squadrons, schedulers are generally pilots, and they prepare the schedule in addition to their other squadron duties. Providing these squadrons with an automated scheduling tool will save schedulers time that they can use for other squadron tasks such as mission preparation, briefings, and debriefings. In this research, a heuristic approach to flight scheduling is presented. GRASP (Greedy Randomized Adaptive Search Procedure) is applied to the weekly pilot scheduling problem. A code for GRASP implementation is written in MATLAB. Two different approaches are used in the analysis. First, the code is run for four weekly schedules for an F-16 squadron of the Turkish Air Force. Then, a weekly flight schedule is created randomly. In the second approach, the created flight schedule is used for three different scenarios that represent possible real-life situations. For all scenarios and real schedules, GRASP performed well and smaller standard deviations in sortie numbers were obtained while keeping all pilots within the currency limit of each mission.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2010
Accession Number
ADA516954

Entities

People

  • Murat Yavuz

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Ground and Sea Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Aircrafts
  • Algorithms
  • Basic Programming Language
  • Debriefing
  • Engineering
  • Flight Training
  • Instructors
  • Mathematical Models
  • Money
  • Night Flight
  • Robotics
  • Scheduling (Production)
  • Simulators
  • Squadrons
  • Standards
  • Training

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Aerospace logistics and air mobility.
  • Aviation Science / Aeronautics.