{"id":26586491,"url":"https://github.com/renatomaynard/gurobi-sensitivity-analysis","last_synced_at":"2026-02-23T09:42:40.446Z","repository":{"id":282313167,"uuid":"948175808","full_name":"RenatoMaynard/Gurobi-Sensitivity-Analysis","owner":"RenatoMaynard","description":"Linear Programming model for Production Planning with full Sensitivity Analysis, including shadow prices, reduced costs, and resource bounds.","archived":false,"fork":false,"pushed_at":"2025-03-14T00:37:29.000Z","size":10,"stargazers_count":19,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-25T15:45:02.707Z","etag":null,"topics":["dual-values","duality","gurobi","gurobipy","linear-programming","lp","mathamtical-optimization","operations-research","optimization","reduced-cost","sensitivity-analysis","shadow-prices"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/RenatoMaynard.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2025-03-13T21:57:51.000Z","updated_at":"2025-04-27T23:24:18.000Z","dependencies_parsed_at":"2025-07-05T22:35:25.730Z","dependency_job_id":"663f369b-0f74-49b5-903b-1e2d8a83a8dc","html_url":"https://github.com/RenatoMaynard/Gurobi-Sensitivity-Analysis","commit_stats":null,"previous_names":["renatomaynard/gurobi-sensitivity-analysis"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/RenatoMaynard/Gurobi-Sensitivity-Analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RenatoMaynard%2FGurobi-Sensitivity-Analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RenatoMaynard%2FGurobi-Sensitivity-Analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RenatoMaynard%2FGurobi-Sensitivity-Analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RenatoMaynard%2FGurobi-Sensitivity-Analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/RenatoMaynard","download_url":"https://codeload.github.com/RenatoMaynard/Gurobi-Sensitivity-Analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RenatoMaynard%2FGurobi-Sensitivity-Analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29741143,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-23T07:44:07.782Z","status":"ssl_error","status_checked_at":"2026-02-23T07:44:07.432Z","response_time":90,"last_error":"SSL_read: 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":["dual-values","duality","gurobi","gurobipy","linear-programming","lp","mathamtical-optimization","operations-research","optimization","reduced-cost","sensitivity-analysis","shadow-prices"],"created_at":"2025-03-23T11:18:21.469Z","updated_at":"2026-02-23T09:42:40.400Z","avatar_url":"https://github.com/RenatoMaynard.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Gurobi Sensitivity Analysis\n\nThis repository demonstrates how to perform **Sensitivity Analysis** in Gurobi for **Linear Programming (LP)** models. The focus is on extracting and interpreting:\n- **Objective coefficient ranges** (how much you can change profit/cost coefficients before the solution changes).\n- **Right-hand side (RHS) ranges** (how much you can change resource limits before the shadow price/dual value changes).\n- **Dual values (Shadow prices)** for constraints.\n- **Reduced costs** for decision variables.\n\n---\n\n## 📊 Features\n\n- **General framework** for performing Sensitivity Analysis on any LP model.\n- Prints **allowable increases and decreases** for:\n  - Objective function coefficients.\n  - RHS of constraints.\n- Computes and displays **dual values (shadow prices)**.\n- Computes **reduced costs** for variables.\n- Fully compatible with **Gurobi** and Python.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frenatomaynard%2Fgurobi-sensitivity-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frenatomaynard%2Fgurobi-sensitivity-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frenatomaynard%2Fgurobi-sensitivity-analysis/lists"}