The Vehicle Scheduling Problem (VSP) represents a pivotal focus within transportation logistics. This study introduces novel prac-tical objectives tailored explicitly for the context of intercity bus opera-tions. The primary objective for VSPs focuses on minimizing fixed costs by minimizing the number of vehicles needed to serve all trips from the timetable. Additionally, the optimization targets reducing operational costs by strategically minimizing deadhead trips. This study introduces innovative metrics pertinent to the complexities of large-scale bus compa-nies, which often rely on subcontractors for service execution. One such objective involves minimizing the number of distinct lines in schedules, particularly crucial in cases where complete lines are entrusted to sub-contractors. This strategic approach fosters schedule homogeneity among subcontractors, streamlining operational logistics and simplifying contin-gency planning in the event of breakdowns. By preemptively optimizing schedules for subcontractors, bus companies can bolster their negotiating leverage and forge more advantageous partnerships. This paper presents a mixed-integer formulation addressing this multi-objective problem, complemented by a computational analysis of real-world instances. The findings underscore the efficacy of the proposed approach in enhancing operational efficiency and strengthening strategic positioning in intercity bus operations.