{"id":18847727,"url":"https://github.com/jacobwilliams/simulated-annealing","last_synced_at":"2026-05-16T16:05:33.890Z","repository":{"id":42700381,"uuid":"205756586","full_name":"jacobwilliams/simulated-annealing","owner":"jacobwilliams","description":"Simulated Annealing with Modern Fortran","archived":false,"fork":false,"pushed_at":"2025-04-20T05:48:59.000Z","size":824,"stargazers_count":27,"open_issues_count":1,"forks_count":5,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-06-25T23:36:25.238Z","etag":null,"topics":["annealing","fortran","optimization","simulated-annealing","stochastic-optimization"],"latest_commit_sha":null,"homepage":"","language":"Fortran","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jacobwilliams.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2019-09-02T01:44:03.000Z","updated_at":"2025-06-03T21:56:16.000Z","dependencies_parsed_at":"2024-01-29T08:10:51.691Z","dependency_job_id":"a49a436b-1d71-4962-a641-115aaedf1298","html_url":"https://github.com/jacobwilliams/simulated-annealing","commit_stats":{"total_commits":37,"total_committers":1,"mean_commits":37.0,"dds":0.0,"last_synced_commit":"57e249338abb97cb23a51018ea9152f5dc5a6c43"},"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/jacobwilliams/simulated-annealing","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacobwilliams%2Fsimulated-annealing","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacobwilliams%2Fsimulated-annealing/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacobwilliams%2Fsimulated-annealing/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacobwilliams%2Fsimulated-annealing/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jacobwilliams","download_url":"https://codeload.github.com/jacobwilliams/simulated-annealing/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jacobwilliams%2Fsimulated-annealing/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29017322,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-02T18:20:26.228Z","status":"ssl_error","status_checked_at":"2026-02-02T18:20:25.361Z","response_time":58,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["annealing","fortran","optimization","simulated-annealing","stochastic-optimization"],"created_at":"2024-11-08T03:09:21.203Z","updated_at":"2026-05-16T16:05:33.870Z","avatar_url":"https://github.com/jacobwilliams.png","language":"Fortran","funding_links":[],"categories":[],"sub_categories":[],"readme":"![simulated-annealing](media/logo.png)\n============\n\nA modern Fortran simulated annealing optimization method.\n\n## Status\n\n[![Language](https://img.shields.io/badge/-Fortran-734f96?logo=fortran\u0026logoColor=white)](https://github.com/topics/fortran)\n[![CI Status](https://github.com/jacobwilliams/simulated-annealing/actions/workflows/CI.yml/badge.svg)](https://github.com/jacobwilliams/simulated-annealing/actions)\n[![GitHub release](https://img.shields.io/github/release/jacobwilliams/simulated-annealing.svg?style=plastic)](https://github.com/jacobwilliams/simulated-annealing/releases/latest)\n[![codecov](https://codecov.io/gh/jacobwilliams/simulated-annealing/branch/master/graph/badge.svg?token=43HK33CSMY)](https://codecov.io/gh/jacobwilliams/simulated-annealing)\n\n## Building\n\nA [Fortran Package Manager](https://github.com/fortran-lang/fpm) manifest file is included, so that the library and test cases can be compiled with FPM. For example:\n\n```\nfpm build --profile release\nfpm test --profile release\n```\n\nTo use `simulated-annealing` within your fpm project, add the following to your `fpm.toml` file:\n```toml\n[dependencies]\nsimulated-annealing = { git=\"https://github.com/jacobwilliams/simulated-annealing.git\" }\n```\n\nTo generate the documentation using [ford](https://github.com/Fortran-FOSS-Programmers/ford), run: ```ford ford.md```\n\n## Features\n\nThe library contains an implementation of a simulated annealing optimization method. See the references for more details. The main class is `simulated_annealing_type`. It also includes the ability to submit function evaluations to parallel workers (the exact parallel implementation is up to the user to implement).\n\nThe library also exports a C interface, which can also be called from Python. A Python package is also included (see the `sa_fortran` class). To use the Python interface, first build and install the shared library using:\n\n```\nfpm install --prefix ./sa_fortran/lib --profile release\n```\n\nThen refer to the two python examples `python_example.py` and `parallel_example.py` for how to use it.\n\n## Using with dask\n\nAn example is given (`dask_parallel_example.py`) of using the parallel interface with [Dask](https://www.dask.org).\n\nExample to run locally with 8 workers:\n\n```\npython dask_parallel_example.py --workers 8 --dimension 2\n```\n\n## Example output\n\n![2D Optimization Visualization](media/report_2d.jpg)\n\n## See also\n\n  *  https://www.netlib.org/opt/simann.f\n\n## Documentation\n\nThe latest API documentation can be found [here](https://jacobwilliams.github.io/simulated-annealing/). This was generated from the source code using [FORD](https://github.com/Fortran-FOSS-Programmers/ford).\n\n## References\n\n  * Corana et al., \"[Minimizing multimodal functions of continuous variables\n    with the \"simulated annealing\" algorithm](https://dl.acm.org/doi/10.1145/29380.29864)\", september 1987\n    (vol. 13, no. 3, pp. 262-280),\n    acm transactions on mathematical software.\n  * Goffe, Ferrier and Rogers, \"[Global optimization of statistical functions\n    with simulated annealing](https://www.sciencedirect.com/science/article/abs/pii/0304407694900388)\", journal of econometrics, vol. 60, no. 1/2,\n    jan./feb. 1994, pp. 65-100.\n  * S. Kirkpatrick, C. D. Gelatt Jr., M. P. Vecchi, \"[Optimization by Simulated Annealing](https://pdfs.semanticscholar.org/e893/4a942f06ee91940ab57732953ec6a24b3f00.pdf)\", Science 13 May 1983, Vol. 220, Issue 4598, pp. 671-680\n  * W. L. Goffe, [SIMANN: A Global Optimization Algorithm using Simulated Annealing](https://www.researchgate.net/publication/24015773_SIMANN_A_Global_Optimization_Algorithm_using_Simulated_Annealing), Studies in Nonlinear Dynamics \u0026 Econometrics, De Gruyter, vol. 1(3), pages 1-9, October 1996.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjacobwilliams%2Fsimulated-annealing","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjacobwilliams%2Fsimulated-annealing","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjacobwilliams%2Fsimulated-annealing/lists"}