{"id":21414533,"url":"https://github.com/rampadc/multi-obj-optim-prob1","last_synced_at":"2026-03-19T20:18:11.311Z","repository":{"id":78893781,"uuid":"326159698","full_name":"rampadc/multi-obj-optim-prob1","owner":"rampadc","description":"IBM ILOG CPLEX problem 1: max strength minimise recruit time","archived":false,"fork":false,"pushed_at":"2021-01-03T15:04:21.000Z","size":7,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-01-23T05:24:32.506Z","etag":null,"topics":["decision-optimization"],"latest_commit_sha":null,"homepage":"https://congx.dev/posts/multiobjective-optimisation-with-ibm-ilog-cplex-1/","language":"AMPL","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/rampadc.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2021-01-02T10:36:25.000Z","updated_at":"2022-05-10T12:31:40.000Z","dependencies_parsed_at":null,"dependency_job_id":"48f02685-16ea-46e1-a1b2-b76eac16e1ab","html_url":"https://github.com/rampadc/multi-obj-optim-prob1","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rampadc%2Fmulti-obj-optim-prob1","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rampadc%2Fmulti-obj-optim-prob1/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rampadc%2Fmulti-obj-optim-prob1/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rampadc%2Fmulti-obj-optim-prob1/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rampadc","download_url":"https://codeload.github.com/rampadc/multi-obj-optim-prob1/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243911244,"owners_count":20367651,"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","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":["decision-optimization"],"created_at":"2024-11-22T18:30:36.498Z","updated_at":"2026-01-03T16:07:14.384Z","avatar_url":"https://github.com/rampadc.png","language":"AMPL","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Multi-objective Optimisation with IBM ILOG CPLEX - Problem 1\n\nThis repository include accompanying code samples to the blog post [Multi-objective Optimisation with IBM ILOG CPLEX - Part 1](https://congx.dev/posts/multiobjective-optimisation-with-ibm-ilog-cplex-1/).\n\n## Getting Started\n\n1. Install the community desktop version for IBM ILOG CPLEX Optimization Studio from [IBM ILOG CPLEX website](https://www.ibm.com/au-en/products/ilog-cplex-optimization-studio).\n2. Clone the repository into a folder. \n3. Once the IDE is installed, navigate to `File \u003e Import \u003e Existing OPL projects`.\n4. Choose the cloned folder as the root directory. Select the project and click `Finish`.\n\nThere are three Run Configurations provided:\n\n- `cp`: uses the `staticLex` method with CP Optimizer\n- `cplex`: uses the `staticLexFull` method with CPLEX Optimizer\n- `cplex-external-main`: uses the `staticLexFull` method with CPLEX Optimizer. This additionally use an external data file to dynamically change the weighting of the optimisation.\n\nRight-click on any of these Run Configurations, and click on `Run this`.\n\nOpen the `Scripting log` panel at the bottom of the perspective to view the results as the optimisation is performed.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frampadc%2Fmulti-obj-optim-prob1","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frampadc%2Fmulti-obj-optim-prob1","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frampadc%2Fmulti-obj-optim-prob1/lists"}