| In recent years, researchers have spent their undivided attention on the field of algo‐ rithms and computer science. Hyper‐Heuristics and Algorithm Selection have been a topic with high potential and research prospects. In this research, a dataset covers 9 NP‐hard problem domains which have 50 instances for each and 18 Hyper‐Heuristic algorithms generated as the performance data. Another feature dataset of 39 perfor‐ mance features, 3 different running time and 4 different acceptance criteria are com‐ bined with the performance data for algorithm selection. Then SUNNY and ASAP are implemented to select the best‐performed algorithms. After the selection is finished, bar charts and radar charts are made for visualization. |
