{"id":13631885,"url":"https://github.com/cbl/informatiCup2022","last_synced_at":"2025-04-17T22:32:16.450Z","repository":{"id":91808847,"uuid":"428461482","full_name":"cbl/informatiCup2022","owner":"cbl","description":"An application of tabu-enhanced genetic search to the railway optimization problem introduced in the informatiCup2022 by the German Informatics Society (:2nd_place_medal:)","archived":false,"fork":false,"pushed_at":"2022-05-13T19:00:00.000Z","size":1017,"stargazers_count":14,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-10-27T21:16:07.192Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Rust","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/cbl.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}},"created_at":"2021-11-16T00:11:02.000Z","updated_at":"2023-07-15T05:32:57.000Z","dependencies_parsed_at":"2024-01-22T01:09:31.798Z","dependency_job_id":"a33837b0-fb8a-4e55-9493-0301838935be","html_url":"https://github.com/cbl/informatiCup2022","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/cbl%2FinformatiCup2022","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbl%2FinformatiCup2022/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbl%2FinformatiCup2022/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cbl%2FinformatiCup2022/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cbl","download_url":"https://codeload.github.com/cbl/informatiCup2022/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":223768665,"owners_count":17199359,"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":[],"created_at":"2024-08-01T22:02:42.484Z","updated_at":"2024-11-08T23:31:46.059Z","avatar_url":"https://github.com/cbl.png","language":"Rust","funding_links":[],"categories":["Rust"],"sub_categories":[],"readme":"# informatiCup2022\n\nAn application of tabu-enhanced genetic search to the railway optimization problem introduced in the [informatiCup2022](https://informaticup.github.io/competition/20-current) by the [German Informatics Society (GI)](https://gi.de/).\n\n:2nd_place_medal: The project was awarded 2nd place. The project presentation can be seen on [youtube](https://www.youtube.com/watch?v=HXvYeeYx5bI\u0026t=3280s).\n\n## Table Of Contents\n\n-   [Introduction](#introduction)\n-   [Usage](#usage)\n    -   [Using cargo](#cargo-usage)\n    -   [Using Docker](#docker-usage)\n    -   [Advance Usage](#advance)\n        -   [Tip](#tip)\n-   [Tests](#tests)\n-   [Documentation](#docs)\n-   [Benchmarks](#benchmarks)\n-   [Coding Style](#coding-style)\n\n\u003ca name=\"introduction\"\u003e\u003c/a\u003e\n\n## Introduction\n\nThis readme contains a usage guide for the program. The theoretical elaboration can be found in the [paper](paper/paper.pdf).\n\n\u003ca name=\"usage\"\u003e\u003c/a\u003e\n\n## Usage\n\n\u003ca name=\"cargo-usage\"\u003e\u003c/a\u003e\n\n### Using cargo\n\nCreate a build using the following command:\n\n```shell\ncargo build --release\n```\n\nThen pass the input model via stdin to the binary:\n\n```shell\ncat test-cases/long/input.txt | ./target/release/rstrain\n```\n\n\u003ca name=\"docker-usage\"\u003e\u003c/a\u003e\n\n### Using Docker\n\nYou may use the docker container to run the programm.\n\nCreate a build first:\n\n```shell\ndocker build . -t rstrain\n```\n\n...and run it via:\n\n```shell\ncat test-cases/long/input.txt | docker run --interactive rstrain\n```\n\n\u003ca name=\"advanced\"\u003e\u003c/a\u003e\n\n### Advanced Usage\n\nThe advanced usage of the program can be printed via the `--help` flag.\n\n```shell\nUSAGE:\n    rstrain [FLAGS] [OPTIONS]\n\nFLAGS:\n    -d, --debug      Prints detailed information about the result\n    -p, --plot       Plots the fitness progress, plots are located in ./plots\n    -h, --help       Prints help information\n    -V, --version    Prints version information\n\nOPTIONS:\n    -s, --tabu-size \u003cTABU\u003e    Size of tabu list, increase for large models (default 8000000)\n    -t, --time \u003cTIME\u003e         Max search duration in milliseconds (default 600000)\n    -m, --t-max \u003cTMAX\u003e        The latest time, increase when a solution with a total delay of 0 cannot be found, default\n                              value is the latest arrival time of all passengers\n```\n\n\u003ca name=\"tip\"\u003e\u003c/a\u003e\n\n#### Tip\n\nThe `--debug` and `--plot` flags come in handy, when it comes to understanding a the progess and performance of a search process for a model.\n\nFor example:\n\n```shell\ncat test-cases/long/input.txt | ./target/release/rstrain --debug --plot\n```\n\nplots the fitness progress into a graph and prints detailed information similar to the following example:\n\n```\n...\n+---------------------+---------+\n| duration            | 0.440s  |\n+---------------------+---------+\n| compared moves      | 1365533 |\n+---------------------+---------+\n| compared moves / ms | 3103    |\n+---------------------+---------+\n| delays              | 0       |\n+---------------------+---------+\n| arrived passengers  | 721/721 |\n+---------------------+---------+\n| t-max               | 6291    |\n+---------------------+---------+\n```\n\n\u003ca name=\"tests\"\u003e\u003c/a\u003e\n\n## Tests\n\nTests can be executed via:\n\n```shell\ncargo test\n```\n\n\u003ca name=\"docs\"\u003e\u003c/a\u003e\n\n## Documentation\n\nA web version of the program's documentation can be created and opened using\nthe following command:\n\n```shell\ncargo doc --open\n```\n\n\u003ca name=\"benchmarks\"\u003e\u003c/a\u003e\n\n## Benchmarks\n\n**Note**: Benchmarks use unstable features of the rust programming languages, which are currently only available on the [nightly channel](https://rust-lang.github.io/rustup/concepts/channels.html#working-with-nightly-rust).\n\nBenchmarks can be run via:\n\n```shell\ncargo bench\n```\n\n\u003ca name=\"coding-style\"\u003e\u003c/a\u003e\n\n## Coding Style\n\nRusts standard code formatter [rustfmt](https://github.com/rust-lang/rustfmt) is used for ensure coding style consistency. It can be run via:\n\n```shell\ncargo fmt\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbl%2FinformatiCup2022","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcbl%2FinformatiCup2022","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcbl%2FinformatiCup2022/lists"}