Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
individual
Campus
Daytona Beach
Authors' Class Standing
Owen Mudgett, Senior
Lead Presenter's Name
Owen Mudgett
Lead Presenter's College
DB College of Arts and Sciences
Faculty Mentor Name
Mihhail Berezovski
Abstract
Scheduling is an intricate problem that encompasses fields like nursing, first responders and pilots. A private company that flies a fleet of 270 jets is looking to improve their current schedule-generating process. This project aims to make a genetic algorithm capable of fast generation of optimized schedules for the company’s pilots. The goal of such an algorithm is to have schedules that both meet work demands while also prioritizing preferences and happiness of the pilots being scheduled. Research on the topic of scheduling algorithms was placed on examples such as the nurse scheduling problem, as many techniques from these types of problems are very relevant to creation of an algorithm. Results of the algorithm will follow tour formats, total work days per bidding period, and other marked days such as training and mandatory off days. The algorithm should ideally give pilots more attractive schedules while optimizing schedules for the company’s needs.
Did this research project receive funding support (Spark, SURF, Research Abroad, Student Internal Grants, Collaborative, Climbing, or Ignite Grants) from the Office of Undergraduate Research?
No
Genetic Scheduling Algorithm for Pilots
Scheduling is an intricate problem that encompasses fields like nursing, first responders and pilots. A private company that flies a fleet of 270 jets is looking to improve their current schedule-generating process. This project aims to make a genetic algorithm capable of fast generation of optimized schedules for the company’s pilots. The goal of such an algorithm is to have schedules that both meet work demands while also prioritizing preferences and happiness of the pilots being scheduled. Research on the topic of scheduling algorithms was placed on examples such as the nurse scheduling problem, as many techniques from these types of problems are very relevant to creation of an algorithm. Results of the algorithm will follow tour formats, total work days per bidding period, and other marked days such as training and mandatory off days. The algorithm should ideally give pilots more attractive schedules while optimizing schedules for the company’s needs.