Preference surveys play a vital role in creating schedules for employees, enhancing job satisfaction and performance. However, conflicting preferences often arise, complicating the scheduling process. This study focuses on identifying contradictory preferences within a dataset provided by a private aviation company, consisting of 10,055 scheduling preferences from 545 flight crew members. To address these challenges, the Contradicting Preference Detection Program (CPDP) was developed. This Python-based tool detects six types of conflicts, including inconsistencies between Weekday, Tour Length, and Date preferences.
Key findings reveal that conflicts often stem from misaligned preferences, such as tour lengths exceeding available workdays or specific dates overlapping with preferred rest periods. The program generates visual and numerical summaries of the contradicting preferences input by crew members. A total of 7,336 conflicts were identified across the dataset, with the highest frequency occurring during peak holiday months.
The CPDP provides insights that have enabled the aviation company to refine its scheduling processes and better align crew schedules with preferences. This study highlights the importance of addressing contradictory preferences to enhance efficiency in scheduling systems.