Centrality measures in social networks are important for understanding how information flows through nodes. Traditional measures like betweenness and closeness combine different factors into one, which may not be ideal for real-world problems. This study introduces a new approach that considers multiple dimensions in centrality measures. They also develop a new closeness measure that not only looks at maximum flow between nodes but also considers communication costs. By modeling the problem as a bi-criteria network flow optimization issue, the researchers show that these new measures can enhance traditional centrality measures.