The article presents a new method to evaluate the efficiency of decision-making units (DMUs) using data envelopment analysis (DEA). The researchers developed a model that addresses issues like inaccurate efficiency estimation and the inability to work with zero or negative data. Their approach includes using common weights, defining virtual ideal and anti-ideal DMUs, and ranking all DMUs in a single run. By applying this model to benchmark examples, the researchers found that it effectively improves efficiency evaluations compared to existing methods.