Multi-objective optimization for the sightseeing bus problem: Trade-off between tourists and operator

The sightseeing bus plays a crucial role in catering to the needs of urban tourist groups. In crafting operational plans, operators aim to make trade-offs between maximizing tourist benefits and minimizing operational costs. This study introduces the multi-objective sightseeing bus problem, encompassing decisions related to bus fleet scheduling, route planning, and tourist assignment. A two-stage multi-objective Adaptive Large Neighborhood Search (MO-ALNS) algorithm is proposed to tackle this multi-objective integer programming model. Customized operators for assignment and routing are devised to augment the algorithm. Numerical experiments demonstrate the algorithm’s effectiveness, offering valuable insights to aid operators in formulating cost-effective sightseeing bus operational plans. Sensitivity analysis underscores a notable correlation between the formulation of the operational plan and the distribution of tourist preferences, spatial distribution of Points of Interest, and vehicle capacity.