Improving Fairness in Airline Integrated Crew Scheduling: Colleague Familiarity and Team Experience Distribution Considerations
针对现有机组排班导致同事频繁更换、经验分布不均的问题，提出多目标优化方法，在满足复杂法规下提升同事熟悉度与团队经验平衡性，经实验验证效果显著。
Psychological health of flight crew is critical to flight safety. Due to job nature (e.g., irregular work schedules, frequent jet lag), colleagues can sometimes outweigh the importance of family for flight crew. Thus, building colleague familiarity and workplace friendship is crucial. However, under the existing air crew scheduling (ACS) approach, crew members face frequent colleague changes and have to work with strangers, causing poor work environments. Besides, reasonable experience level distributions in crew teams are also crucial for crew satisfaction. However, the existing ACS approach frequently produces crew teams with unbalanced distributions of experience levels (e.g., all members from various ranks have lower-end experience levels within the qualified range). To overcome these drawbacks, this study develops a novel multi-objective ACS approach that can improve colleague familiarity (i.e., increase the chance for crew members to work together) and form crew teams with more reasonable and balanced experience level distributions. An evolutionary algorithm that incorporates the hyperplane separation and heuristic search strategy is proposed to derive Pareto solutions. The proposed ACS approach is examined on long-haul flight schedules which impose more complicated crew work/rest regulations. Extensive computational experiments with subsequent analysis validate the proposed method's effectiveness, showing an impressive improvement in colleague familiarity (1989.45%,