{"url":"/dataset/floripasat-milps","name":"FloripaSat MILPs","full_name":null,"description_markdown":"This dataset contains several instances of the Offline Nanosatellite Task Scheduling (ONTS) problem, based on the parameters of the FloripaSat-1 mission. Each instance (.json file) is paired with a (quasi-)optimal solution vector (_opt.npz file) and the 500 best solutions found (_sols.npz file).\r\n\r\nIn https://github.com/brunompacheco/sat-gnn you can find the code used to generate the instances, load them, and compute the results in the .npz files.","description_withheld":null,"homepage":"https://doi.org/10.5281/zenodo.8356797","introduced_date":"2023-03-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/a-graph-neural-network-approach-to","title":"Graph Neural Networks for the Offline Nanosatellite Task Scheduling Problem","first_author":"Bruno Machado Pacheco","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["FloripaSat MILPs"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}