{"url":"/dataset/simulation-inputs-outputs","name":"RSM-based multi-objective optimization using desirability functions","full_name":null,"description_markdown":"The following files contains the simulation inputs and outputs for conducting the multi-objetive optimization of thermal comfort and dyalight with the Response Surface Methodology. This files feed are needed for running the R script/code as well as the datasets are contained in the Github repository.","description_withheld":null,"homepage":"","introduced_date":"2024-09-12","introduced_date_note":null,"introduced_by":{"paper":"/paper/response-surface-methodology-coupled-with","title":"Response Surface Methodology coupled with desirability functions for multi-objective optimization: minimizing indoor overheating hours and maximizing useful daylight illuminance","first_author":"Juan Gamero-Salinas","url":null},"license":{"name":"CC BY 4.0","url":"http://creativecommons.org/licenses/by/4.0/"},"modalities":[{"name":"Tabular","url":"/datasets/modality/tabular"}],"tasks":[{"name":"Multiobjective Optimization","url":"/task/multiobjective-optimization","datasets_with_task":"/datasets/task/multiobjective-optimization"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["RSM-based multi-objective optimization using desirability functions"],"data_loaders":[{"repo":"https://github.com/juan-gamero-salinas/rsm-thermal-daylight-optimization","url":"https://github.com/juan-gamero-salinas/rsm-thermal-daylight-optimization","frameworks":[]}],"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."}