{"id":19722032,"url":"https://github.com/sensoranalyticsaus/simple_ga_1.1","last_synced_at":"2026-06-07T22:33:30.787Z","repository":{"id":224468573,"uuid":"540203454","full_name":"SensorAnalyticsAus/Simple_GA_1.1","owner":"SensorAnalyticsAus","description":"A Simple Genetic Algorithm","archived":false,"fork":false,"pushed_at":"2022-09-24T01:32:33.000Z","size":111,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-02-28T00:31:49.469Z","etag":null,"topics":["artificial-intelligence","genetic-algorithm","machine-learning-algorithms"],"latest_commit_sha":null,"homepage":"","language":"C","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/SensorAnalyticsAus.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"License.md","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}},"created_at":"2022-09-22T23:19:52.000Z","updated_at":"2023-11-23T11:59:20.000Z","dependencies_parsed_at":null,"dependency_job_id":"e2db8c02-dcb8-44aa-8b31-6d51ffe5feed","html_url":"https://github.com/SensorAnalyticsAus/Simple_GA_1.1","commit_stats":null,"previous_names":["sensoranalyticsaus/simple_ga_1.1"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/SensorAnalyticsAus/Simple_GA_1.1","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SensorAnalyticsAus%2FSimple_GA_1.1","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SensorAnalyticsAus%2FSimple_GA_1.1/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SensorAnalyticsAus%2FSimple_GA_1.1/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SensorAnalyticsAus%2FSimple_GA_1.1/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/SensorAnalyticsAus","download_url":"https://codeload.github.com/SensorAnalyticsAus/Simple_GA_1.1/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/SensorAnalyticsAus%2FSimple_GA_1.1/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34041087,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-07T02:00:07.652Z","response_time":124,"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":["artificial-intelligence","genetic-algorithm","machine-learning-algorithms"],"created_at":"2024-11-11T23:16:16.037Z","updated_at":"2026-06-07T22:33:30.768Z","avatar_url":"https://github.com/SensorAnalyticsAus.png","language":"C","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Simple Genetic Algorithm (SGA)\n## Compile\n##### One of the following commands will compile the simple genetic algorithm executable in the downloaded folder.\n\u003cpre\u003e\u003ccode\u003e \nmake sga2\nmake sga3\n\u003c/code\u003e\u003c/pre\u003e\n##### The SGA binaries for the sample objective function codes, *obj2.c* and *obj3.c*, will be *sga2* and *sga3* respectively.\n## Run\n##### The compiled code is run by writing an objective function to be optimised by SGA in *C*, two such sample objective function codes are provided in the downloaded folder. \n##### File *sga3.var* contains the SGA parameters. These are explained in **Simple Genetic Algorithm Explainer.pdf** [Section 4]. Results are stored in *genout.dat*.\n\n## Acknowledgement\n##### This C code is based upon D.E. Goldberg's Genetic Algorithms in Search, Optimisation and Machine Learning 1989.\n\n##### ©SAA 2022\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsensoranalyticsaus%2Fsimple_ga_1.1","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsensoranalyticsaus%2Fsimple_ga_1.1","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsensoranalyticsaus%2Fsimple_ga_1.1/lists"}