Spatial Input Dataset for Obstacle-Aware Multi-Target Routing in Campus Logistics

This dataset provides the spatial input data used in the study “AI-Enabled Decision-Making for Sustainable and Resource-Efficient Campus Logistics: Obstacle-Aware Multi-Target Routing Using an Improved Mayfly Optimization Algorithm.” It includes the synthetic G40 benchmark grid and fixed task-node coordinates, as well as the processed G-real campus grid and fixed task-node coordinates used for application-level validation. The G40 grid is 40 × 40 and the G-real grid is 1100 × 1200. In both grid files, 0 denotes a traversable cell and 1 denotes an obstacle or non-traversable cell. The G40 task nodes were generated once and then kept fixed across all algorithms and runs to ensure consistent comparison. The repository also includes a README file describing the dataset structure and encoding. These data are provided to support transparency and reproducibility of the spatial modeling and routing experiments reported in the associated study.