Graph Instance Landscapes: When Structural Similarity Does (Not) Reflect Shortest-Path Performance
Researchers have developed a new method for benchmarking shortest-path algorithms by analyzing graph structures. This approach embeds graphs into a feature space and clusters them to identify regions of similar structure, which are then used to evaluate algorithm performance. The study examined Erdos-Renyi graphs, random geometric graphs, and road networks, testing algorithms like Dijkstra, bidirectional Dijkstra, and A*. Findings indicate that while graph generators create stable structural regions, performance similarity does not always align with structural similarity, and different benchmark families occupy distinct regions. AI