In graph theory, the least-cost path is discovered by searching the shortest path between a start node and destination node. The least cost is calculated as a one-dimensional value that represents the difference in distance or price between two nodes, and the nodes and edges that comprise the lowest sum of costs between the linked nodes is the shortest path. However, it is difficult to determine the shortest path if each node has multiple attributes because the number of cost types that can appear is equal to the number of attributes. In this paper, a shortest path search scheme is proposed that considers multiple attributes using the Euclidean distance to satisfy various user requirements. In simulation, we discovered that the shortest path calculated using one-dimensional values differs from that calculated using the Euclidean distance for two-dimensional attributes. The user’s preferences are reflected in multi attributes and it was different from one-dimensional attribute. Consequently, user requirements could be satisfied simultaneously by considering multiple attributes.