Is this project an undergraduate, graduate, or faculty project?
Undergraduate
Project Type
group
Campus
Daytona Beach
Authors' Class Standing
Jessica Christa Wira, Senior Caelin Sergent, Senior Trent Bazemore, Junior
Lead Presenter's Name
Jessica Christa Wira
Lead Presenter's College
DB College of Arts and Sciences
Faculty Mentor Name
Dr. Mihhail Berezovski
Abstract
Flexjet Inc. is a private aviation company that supports the needs of multiple established private jet brands such as providing crew management and scheduling. Planning crew schedules is one of the many challenges they face due to the complex set of requirements such as ensuring that there are enough crew available to meet customers’ demands. Additionally, crew preferences are also considered in the scheduling process, and these are collected by a crew-facing mobile application. However, Flexjet’s crew services team found many conflicts present in the preferences input which should have been caught when entering them. Therefore, this research aims to develop a crew preference adaptive monitoring system that would track a set of crew preferences, identify if there are any conflicts, and return the conflicting preferences along with supporting information. Our research has concluded that most crew members had conflicts with their preferred workdays in each 28-day bidding period and most conflicts occurred within holiday periods.
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
Flexjet Crew Preferences Conflict Adaptive Monitoring
Flexjet Inc. is a private aviation company that supports the needs of multiple established private jet brands such as providing crew management and scheduling. Planning crew schedules is one of the many challenges they face due to the complex set of requirements such as ensuring that there are enough crew available to meet customers’ demands. Additionally, crew preferences are also considered in the scheduling process, and these are collected by a crew-facing mobile application. However, Flexjet’s crew services team found many conflicts present in the preferences input which should have been caught when entering them. Therefore, this research aims to develop a crew preference adaptive monitoring system that would track a set of crew preferences, identify if there are any conflicts, and return the conflicting preferences along with supporting information. Our research has concluded that most crew members had conflicts with their preferred workdays in each 28-day bidding period and most conflicts occurred within holiday periods.