Collaborative scheduling of shared electric vehicle charging stations
研究两家公司协调充电以最小化各自成本并实现高效公平结果的协同调度问题，提出平衡边界框法（B3M）生成代表性最优解集，并应用合作博弈得出可行决策，数值实验表明该方法在保持前沿完整性的同时大幅缩短计算时间。
Electric vehicle charging faces challenges of high infrastructure costs and low utilization. Shared charging among fleet operators offers a sustainable alternative. This study formulates a collaborative scheduling problem in which two companies coordinate charging to minimize their individual costs while achieving efficient and equitable outcomes. A bi-objective optimization framework is developed, proposing the Balanced Bounding Box Method (B3M) to generate a representative subset of globally optimal solutions with substantially reduced computational effort. Cooperative bargaining is then applied to derive an actionable final decision from the efficient frontier. Numerical results show that this framework maintains frontier integrity while cutting computation time. Beyond improving decision efficiency, the study offers insights into how transparent and equitable solution selection can sustain long-term collaboration among operators. The framework provides practical guidance to improve charger utilization and reduce system costs, supporting more sustainable use of existing infrastructure.