{"id":20393331,"url":"https://github.com/dmalyuta/explicit_hybrid_mpc","last_synced_at":"2025-08-25T12:19:32.449Z","repository":{"id":95511802,"uuid":"170376823","full_name":"dmalyuta/explicit_hybrid_mpc","owner":"dmalyuta","description":"Approximate Multiparametric Mixed-integer Convex Programming","archived":false,"fork":false,"pushed_at":"2019-05-16T07:57:27.000Z","size":1510,"stargazers_count":14,"open_issues_count":2,"forks_count":4,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-19T16:36:26.798Z","etag":null,"topics":["control-systems","convex-optimization","high-performance-computing","mixed-integer-programming","mpi","optimization","parallel-computing"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dmalyuta.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2019-02-12T19:19:18.000Z","updated_at":"2024-12-21T14:39:23.000Z","dependencies_parsed_at":null,"dependency_job_id":"6db9b4df-e9ff-494e-bbb2-509794eb31e7","html_url":"https://github.com/dmalyuta/explicit_hybrid_mpc","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/dmalyuta/explicit_hybrid_mpc","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmalyuta%2Fexplicit_hybrid_mpc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmalyuta%2Fexplicit_hybrid_mpc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmalyuta%2Fexplicit_hybrid_mpc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmalyuta%2Fexplicit_hybrid_mpc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dmalyuta","download_url":"https://codeload.github.com/dmalyuta/explicit_hybrid_mpc/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dmalyuta%2Fexplicit_hybrid_mpc/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272063456,"owners_count":24866727,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-25T02:00:12.092Z","response_time":1107,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["control-systems","convex-optimization","high-performance-computing","mixed-integer-programming","mpi","optimization","parallel-computing"],"created_at":"2024-11-15T03:48:17.363Z","updated_at":"2025-08-25T12:19:32.400Z","avatar_url":"https://github.com/dmalyuta.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Approximate Multiparametric Mixed-integer Convex Programming\n\n\u003cp align=\"center\"\u003e\n\t\u003cimg width=\"500\" src=\"/figures/readme_image.png?raw=true\"\u003e\n\u003c/p\u003e\n\u003cp align=\"center\" width=\"600\"\u003e\nFigure: control evaluation time. Bars show the mean while error bars shown the\nminimum and maximum values. The explicit implementation is up to three orders of\nmagnitude faster than on-line optimization.\n\u003c/p\u003e\n\n## General Description\n\nThis repository implements the algorithm for generatic suboptimal explicit\nsolutions of multiparametric mixed-integer convex programs, submitted to [IEEE\nControl Systems Letters](http://ieee-cssletters.dei.unipd.it/index.php). The\nalgorithm can be run either locally or on a cluster via `mpirun`.\n\n``` \n@ARTICLE{Mayuta2019,\n       author = {{Malyuta}, Danylo and {A\\c{c}{\\i}kme\\c{s}e}, Beh\\c{c}et},\n        title = {Approximate Multiparametric Mixed-integer Convex Programming},\n      journal = {arXiv e-prints},\n     keywords = {Mathematics - Optimization and Control},\n         year = \"2019\",\n        month = \"Feb\",\n          eid = {arXiv:1902.10994},\n        pages = {arXiv:1902.10994},\narchivePrefix = {arXiv},\n       eprint = {1902.10994},\n primaryClass = {math.OC},\n       adsurl = {https://ui.adsabs.harvard.edu/abs/2019arXiv190210994M},\n      adsnote = {Provided by the SAO/NASA Astrophysics Data System}\n}\n```\n\n## Requirements\n\nTo run the code, you must have Python 3.7.2 and [MOSEK\n9.0.87](https://www.mosek.com/downloads/) installed. To install Python and other\ndependenies (except MOSEK) on Ubuntu, we recommend that you install [Anaconda\nfor Python 3.7](https://www.anaconda.com/distribution/) and then execute (from\ninside this repository's directory):\n\n```\n$ conda create -n py372 python=3.7.2 anaconda # Answer yes to everything\n$ source activate py372\n$ pip install -r requirements.txt\n```\n\n## Instructions\n\nPartitioning jobs are created through `make_jobs.sh`. Run\n\n```\nbash make_jobs.sh -h\n```\nfor more information. The job files are stored in the `./runtime` directory.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmalyuta%2Fexplicit_hybrid_mpc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdmalyuta%2Fexplicit_hybrid_mpc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdmalyuta%2Fexplicit_hybrid_mpc/lists"}