The article introduces a new method for ranking extremely efficient decision-making units in data envelopment analysis. The researchers aim to address the challenges of existing ranking techniques by minimizing the distance between the unit being evaluated and a virtual unit. This approach helps to overcome issues of infeasibility and unboundedness in DEA ranking methods.