Collaborative scheduling of shared electric vehicle charging stations

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.