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Bots"},"license":"MIT","homepage":"https://github.com/pwgbots/linny-r#readme","keywords":["executable","graphical modeling language","mixed integer linear programming","optimization","simulation","unit commitment","industrial ecology","linearized power flow","loss approximation","generation expansion","grid expansion"],"repository":{"type":"git","url":"git+https://github.com/pwgbots/linny-r.git"},"description":"Executable graphical language with WYSIWYG editor for MILP models","maintainers":[{"name":"pwgbots","email":"p.w.g.bots@tudelft.nl"}],"readme":"<img src=\"static/images/logo.png\" height=\"55px\" alt=\"Linny-R\">\r\n\r\nLinny-R is an executable graphical specification language for mixed integer \r\n<a href=\"https://en.wikipedia.org/wiki/Linear_programming\"\r\n   target=\"_blank\">linear programming</a> (MILP) problems, especially\r\n<a href=\"https://en.wikipedia.org/wiki/Unit_commitment_problem_in_electrical_power_production\"\r\n   target=\"_blank\">unit commitment problems</a>\r\n(UCP) and\r\n<a href=\"https://en.wikipedia.org/wiki/Generation_expansion_planning\"\r\n   target=\"_blank\">generation expansion planning</a> (GEP).\r\n\r\nThe graphical language and WYSIWYG model editor are developed by **Pieter Bots**\r\nat <a href=\"https://tudelft.nl\" target=\"_blank\">Delft University of Technology</a>.\r\n \r\nOriginally implemented in Delphi Pascal, Linny-R is now developed in\r\nHTML+CSS+JavaScript so as to be platform-independent and 100% transparent\r\nopen source (under the MIT license). The software comprises a server that\r\nruns on **Node.js**, and a graphical user interface (GUI) that runs in any\r\nmodern browser.\r\n\r\nThese <a href=\"https://sysmod.tbm.tudelft.nl/linny-r/docs/?68\"\r\n         target=\"_blank\">instruction videos</a> published on YouTube give\r\nan idea of what Linny-R can do.\r\n\r\nUser documentation for Linny-R is still scant. A book \"Modelling and\r\nsimulation with Linny-R\" will be published by TU Delft OPEN in 2026.\r\nMeanwhile, you can consult the official user documentation site\r\n<a href=\"https://linny-r.info\" target=\"_blank\">https://linny-r.info</a>.\r\nTechnical documentation will be developed in due time on GitHub:\r\nhttps://github.com/pwgbots/linny-r/wiki\r\n\r\n## Installing Node.js\r\n\r\nLinny-R is developed as a JavaScript package, and requires that **Node.js**\r\nis installed on your computer. This software can be downloaded from\r\n<a href=\"https://nodejs.org\" target=\"_blank\">https://nodejs.org</a>. \r\nMake sure that you choose the correct installer for your computer.\r\nLinny-R is developed using the _current_ release. Presently (January 2026)\r\nthis is 25.2.1. \r\n\r\nRun the installer and accept the default settings.\r\nThere is <u>**no**</u> need to install the optional _Tools for Native Modules_.\r\n\r\nOpen the Command Line Interface (CLI) of your computer. \r\nOn macOS, this will be `Terminal`, on Windows `Command Prompt`. \r\nVerify the installation by typing:\r\n\r\n``node --version``\r\n\r\nThe response should be the version number of Node.js, for example: v25.2.1.\r\n\r\n## Installing Linny-R\r\nIt is advisable to install Linny-R in a directory on your computer, **not**\r\nin a cloud. \r\n\r\nIn this installation guide, the path to this directory is denoted by `Linny-R`,\r\nso in all commands you should replace this with the actual directory path.\r\nOn a Windows machine the suggested path is `C:\\Users\\(your user name)\\Linny-R`,\r\nand on a macOS machine `/Users/(your user name)/Linny-R`.\r\n\r\nTo install Linny-R in this directory, first change to the parent directory\r\nlike so:\r\n\r\n``cd /Users/(your user name)``\r\n\r\nThen create the `Linny-R` directory:\r\n\r\n``mkdir Linny-R``\r\n\r\nthen change to it:\r\n\r\n``cd Linny-R``\r\n\r\nand then type at the command line prompt: \r\n\r\n``npm install --prefix . linny-r``\r\n\r\n> [!IMPORTANT]\r\n> The spacing around the dot is essential. Type the command in lower case.\r\n\r\n> [!IMPORTANT]\r\n> Unless you _really_ know what you are doing, do **not** move or rename\r\n> your Linny-R directory or change its contents. If for some reason Linny-R\r\n> does not work, remove _all_ Linny-R software from your machine, and then\r\n> install it anew, following the procedure described above.\r\n\r\n#### Updating to the latest version of Linny-R\r\n\r\nWhen a newer version has been released, Linny-R will prompt you to update\r\nautomatically. Click on the link in this prompt to see the release notes\r\non GitHub and find out about new features and bug fixes. When you click on\r\nthe _OK_ button, Linny-R will shut down its local server script, and then\r\nthe launch script should perform the `npm update` command and then restart\r\nthe server script. Your browser will prompt you to close its current tab,\r\nand then Linny-R should reappear in a new browser tab or window.\r\n\r\n> [!NOTE]\r\n> The built-in updating function of Linny-R will _**not**_ automatically\r\n> upgrade to a new _major_ version. To update from a version like 2.1.x to\r\n> a version like 3.0.x, you have to open a command line interface\r\n> (`Command Prompt` or `Terminal`), change to your Linny-R directory, and\r\n> then type `npm install linny-r@3`. This should perform the upgrade.\r\n> You can then launch Linny-R as usual by typing `linny-r` (Windows) or\r\n> `./linny-r.command` (macOS).\r\n\r\n#### Installing and using an earlier version of Linny-R\r\n\r\nBy default, **npm** will install the latest release of the Linny-R software.\r\nAs this software is developed as part of academic research, new features\r\nare added without rigorous testing. Although much effort is dedicated to\r\nmaintaining upward and downward compatibility, you may find that the latest\r\nversion does not work as well for you as some earlier version. To re-install\r\nan earlier release, for example version 2.1.9, open the CLI, change to your\r\n`Linny-R` directory, and then type:\r\n\r\n``npm install linny-r@2.1.9``\r\n\r\n> [!NOTE]\r\n> This will overwrite the contents of the `node_modules` directory, but\r\n> it will not affect the files in your user space.\r\n\r\nIf you prefer to have multiple versions of Linny-R on your computer, you\r\ncan create a separate directory for a specific version, then change to this\r\ndirectory and type:\r\n\r\n``npm install --prefix . linny-r@2.1.9``  &larr; _replace_ `2.1.9` _by the version of your choice_\r\n\r\n> [!NOTE]\r\n> To run a specific version in your browser, you must start the server from\r\n> the directory where you installed this version.\r\n> Should you wish to run two different versions concurrently, you must use\r\n> the `port=[number]` option when you start the server for the second version.\r\n\r\n## Configuring the MILP solver\r\n\r\nLinny-R presently supports five MILP solvers: Gurobi, MOSEK, CPLEX, SCIP\r\nand LP_solve. Gurobi, MOSEK and CPLEX are _considerably_ more powerful than\r\nthe open source solvers SCIP and LP_solve, but they require a license.\r\nAcademic licenses can be obtained by students and staff of eligible\r\ninstitutions.\r\n\r\n> [!IMPORTANT]\r\n> When installing a solver, it is advisable to accept the default file\r\n> locations that are proposed by the installer.\r\n> After installation, do **not** move files to some other directory,\r\n> as this is bound to cause problems.\r\n\r\n#### Installing Gurobi\r\n\r\nThe software you need to install is **Gurobi Optimizer**.\r\nMore information on how to obtain a license, and instructions for installing\r\nGurobi on your computer can be obtained via this URL:\r\n<a href=\"https://www.gurobi.com/academia/academic-program-and-licenses/\"\r\n   target=\"_blank\">https://www.gurobi.com/academia/academic-program-and-licenses/</a>\r\nThe recommended license type is the **Academic Named-User License**.\r\n\r\nWhen running a model, Linny-R will try to execute the command line application\r\n`gurobi_cl`. It will look for this application in the directory specified in\r\nthe environment variable PATH on your computer.\r\n\r\n#### Installing CPLEX\r\n\r\nThe software you need to install is **CPLEX**.\r\nMore information on how to obtain a license, and instructions for installing\r\nCPLEX on your computer can be obtained via this URL:\r\n<a href=\"https://www.ibm.com/products/ilog-cplex-optimization-studio\"\r\n   target=\"_blank\">https://www.ibm.com/products/ilog-cplex-optimization-studio</a>\r\n\r\nWhen running a model, Linny-R will try to execute the command line application\r\n`cplex`. It will look for this application in the directory specified in the\r\nenvironment variable PATH or more specifically in the environment variable\r\nCPLEX_STUDIO_BINARIES<em>nnnn</em> (where _nnnn_ denotes the CPLEX version\r\nnumber) on your computer.\r\n\r\n#### Installing MOSEK\r\n\r\nThe software you need to install is **MOSEK**.\r\nMore information on how to obtain a license, and instructions for installing\r\nMOSEK on your computer can be obtained via this URL:\r\n<a href=\"https://www.mosek.com/resources/getting-started/\"\r\n   target=\"_blank\">https://www.mosek.com/resources/getting-started/</a>\r\n\r\nWhen running a model, Linny-R will try to execute the command line application\r\n`mosek`. It will look for this application in the directory specified in the\r\nenvironment variable PATH on your computer.\r\n\r\n#### Installing SCIP\r\n\r\nThe SCIP software is open source. Instructions for installation can be found\r\nvia this URL: <a href=\"https://scipopt.org/doc/html/INSTALL.php\"\r\n                 target=\"_blank\">https://scipopt.org/doc/html/INSTALL.php</a>\r\n\r\nWhen running a model, Linny-R will try to execute the command line application\r\n`scip`. It will look for this application in the directory specified in the\r\nenvironment variable PATH on your computer.\r\n\r\n#### Installing LP_solve\r\n\r\nThe LP_solve software is open source and can be downloaded via this URL:\r\n<a href=\"https://sourceforge.net/projects/lpsolve\"\r\n   target=\"_blank\">https://sourceforge.net/projects/lpsolve</a>\r\n\r\nTo facilitate installation, the executable files for Windows and macOS can\r\nbe downloaded from the Linny-R website at Delft University of Technology:\r\n<a href=\"https://sysmod.tbm.tudelft.nl/linny-r/lp_solve\"\r\n   target=\"_blank\">https://sysmod.tbm.tudelft.nl/linny-r/lp_solve</a>\r\n\r\nThere you will find links to download LP_solve applications that have been\r\ncompiled for different platforms. If you do not know which platform to choose,\r\nrun Linny-R as described below, and the platform will be listed in its output.\r\nIf no matching LP_solve version is listed, you can try to compile the software\r\nfrom its source. How to do this is explained on the page \"Installing LP_solve\r\non a Mac\" on the Linny-R documentation site:\r\n<a href=\"https://linny-r.info\" target=\"_blank\">https://linny-r.info</a> \r\n\r\nWhen you have downloaded the file (just `lp_solve` for macOS, `lp_solve.exe`\r\nfor Windows), you must copy or move this file to your `Linny-R` directory,\r\nas this is where Linny-R will look for it when it does not find one of the\r\nother solvers.\r\n\r\nOn a macOS machine, you must then make the file `lp_solve` executable.\r\nOpen `Terminal` and change to your Linny-R directory, and then type:\r\n\r\n``chmod +x lp_solve``\r\n\r\nWhen you then type:\r\n\r\n``./lp_solve -h``\r\n\r\na window may appear that warns you that the software may be malicious.\r\nTo allow running LP_solve, you must then go to _Security & Privacy_ (via\r\n_System Preferences_) and there click the _Open Anyway_ button in the _General_\r\npane to confirm that you wish to use LP_solve. Then return to `Terminal`\r\nand once more type `./lp_solve -h`. The response should then be a listing\r\nof all the command line options of LP_solve. If you reach this stage,\r\nLinny-R will be able to run LP_solve.\r\n\r\n## Running Linny-R\r\n\r\nOn a Windows machine, open `Command Prompt`, change to your Linny-R\r\ndirectory and type:\r\n\r\n``linny-r``\r\n\r\nOn a macOS machine, open `Terminal`, change to your Linny-R directory\r\nand type:\r\n\r\n``./linny-r.command``\r\n\r\nThis should run the launch script for Linny-R, which will start the\r\nlocal server script that connects your browser with the solver. \r\nMeanwhile, your default web browser should have opened a tab for the local\r\nserver URL, which by default will be http://127.0.0.1:5050.\r\nThe Linny-R GUI should show in your browser window, while in the CLI you\r\nshould see a long series of server log messages like:\r\n\r\n<pre>\r\n[2025-10-01 22:55:17] Static file: /index.html\r\n[2025-10-01 22:55:17] Static file: /scripts/iro.min.js\r\n[2025-10-01 22:55:17] Static file: /images/open.png\r\n... etc.\r\n</pre>\r\n\r\n> [!IMPORTANT]\r\n> Do **not** close the CLI. If you do, the Linny-R GUI may still be\r\n> visible in your browser, but you will be warned that it cannot connect\r\n> to the server (at 127.0.0.1:5050). This means that you have to restart\r\n> Linny-R as described above.\r\n\r\nAfter loading into the browser, Linny-R will try to connect to the solver.\r\nIf successful, a notification (blue background) will appear on the status\r\nbar at the bottom of the window, stating the name of the solver.\r\n\r\nYou can then test the GUI by creating a simple model.\r\nMake one that has at least one process that outputs a product, \r\nand this product must have a price or a set lower bound, otherwise the\r\nmodel will have no objective function.\r\nThen click on the _Solve_ button\r\n<img src=\"static/images/solve.png\" height=\"18px\">\r\nat the bottom of the left-hand tool bar.\r\nThe Linny-R icon in the upper left corner should start rotating, while the\r\nstatus bar at the bottom should display:\r\n\r\n<pre>\r\nSolving block 1 of 1\r\n</pre>\r\n\r\nFor a small test model, this message should appear only very briefly,\r\nand then the diagram will be updated to reflect the obtained solution.\r\nMeanwhile, in the CLI, you should see a server log message like:\r\n\r\n<pre>\r\nSolve block 1 a with SCIP\r\n</pre>\r\n\r\nTo end a modeling session, you can shut down the server by clicking on the\r\nlocal host icon <img src=\"static/images/host-logo.png\" height=\"18px\">\r\nin the upper right corner of the Linny-R GUI in your browser,\r\nconfirming that you want to leave, and then closing your browser (tab).\r\nIf you do not shut down the server from the browser, you can also stop the\r\nserver by repeatedly pressing `Ctrl+C` in the CLI.\r\n\r\n## Click-start for Linny-R\r\n\r\nWhen `npm` installs the Linny-R package, it creates a script file in your\r\nLinny-R directory that launches Linny-R. On a macOS machine, this will be\r\nthe shell script `linny-r.command`, on a Windows machine the batch script\r\n`linny-r.bat`. When you create a desktop shortcut to this script, this will\r\nallow you to click-start Linny-R. \r\n\r\nHow you can create a shortcut icon for Linny-R on your desktop depends on\r\nthe type of computer you use.\r\n\r\nOn a Windows machine, open the `File Explorer`, select your Linny-R folder,\r\nright-click on the batch file `linny-r.bat`, and select the _Create shortcut_\r\noption. Then right-click on the shortcut file to edit its properties, and\r\nclick the _Change Icon_ button. The dialog that then appears will allow\r\nyou to go to the sub-folder `node_modules\\linny-r\\static\\images`, where\r\nyou should select the file `linny-r.ico`. Finally, rename the shortcut to\r\n`Linny-R` and move or copy it to your desktop.\r\n\r\nOn a macOS machine, open `Terminal` and change to your Linny-R directory,\r\nand then type:\r\n\r\n``chmod +x linny-r.command``\r\n\r\nto make the script file executable. To set the icon, use `Finder` to open\r\nthe folder that contains the file `linny-r.command`, click on its icon\r\n(which still is plain) and open the _Info dialog_ by pressing ``Cmd+I``.\r\nThen open your Linny-R folder in `Finder`, change to the sub-folder\r\n`node_modules/linny-r/static/images`, and from there drag/drop the file\r\n`linny-r.icns` on the icon shown in the top left corner of the _Info dialog_.\r\n\r\n## Command line options\r\n\r\nYou can customize Linny-R by adding more arguments to the `node` command\r\nin the launch script:\r\n\r\n<pre>\r\nlaunch             to automatically launch Linny-R in your default browser\r\nport=[number]      to overrule the default port number (5050)\r\nsolver=[name]      to overrule the default sequence (Gurobi, MOSEK, CPLEX, SCIP, LP_solve)\r\nworkspace=[path]   to overrule the default path for the user directory\r\n</pre>\r\n\r\n> [!NOTE]\r\n> When configuring Linny-R for a network environment where individual users\r\n> each have their personal work space (e.g., a virtual drive U:), you **must**\r\n> edit the launch script file, adding the argument `workspace=path/to/workspace`\r\n> to the `node` command. This will instruct Linny-R to create the `user`\r\n> directory in this workspace directory instead of the Linny-R directory.\r\n\r\n## User workspace\r\n\r\nThe user workspace is created when the server is run for the first time.\r\nThe sub-directories of this directory `user` are used by Linny-R to store files.\r\n\r\n* `autosave` will contain models that have been _auto-saved_ \r\n* `channel` will be used to interact with Linny-R via its _Receiver_ \r\n* `data` will be used by the _Dataset Manager_ to locate datasets for which\r\n  a path has been specified\r\n* `models` will contain models that you saved by clicking the _Save_ button\r\n   or using the keyboard shortcut `(Shift) Ctrl-S`.\r\n* `reports` will contain text files with time series data and statistics in\r\n  tab-separated format that can be imported or copy/pasted into Excel\r\n* `solver` will contain the files that are exchanged with the Mixed Integer\r\n  Linear Programming (MILP) solver (the names of the files that will appear\r\n  in this directory may vary, depending on the MILP-solver you use)\r\n\r\n> [!NOTE]\r\n> By default, the `user` directory is created in your `Linny-R` directory.\r\n> You can overrule this by starting the server with the `workspace=[path]`\r\n> option. This will create a new, empty workspace in the specified path.\r\n> It will **not** affect or duplicate information from existing workspaces.\r\n\r\n## Using Linny-R console\r\n\r\nThe console-only version of Linny-R allows you to run a Linny-R model without\r\na web browser. This may be useful when you want run models from a script\r\n(shell script, Python, ...). If you open a CLI box, change to your `Linny-R`\r\ndirectory, and then type:\r\n\r\n``node node_modules/linny-r/console``  _(on Windows, use backslashes)_\r\n\r\nyou will see the command line options that allow you to run models in various\r\nways.\r\n\r\n> [!NOTE]\r\n> The console-only version is still in development, and does not provide\r\n> all functions yet.\r\n\r\n## Checking your Linny-R configuration\r\n\r\nAfter installation has completed, `Linny-R` should have this directory tree\r\nstructure:\r\n\r\n<pre>\r\nLinny-R\r\n |\r\n +-node_modules\r\n    |\r\n    +-@xmldom\r\n    |\r\n    +-linny-r\r\n       |\r\n       +-static\r\n          |\r\n          +-fonts\r\n          |\r\n          +-images\r\n          |\r\n          +-scripts\r\n          |\r\n          +-sounds\r\n</pre>\r\n\r\n`Linny-R` should contain two JSON files `package.json` and `package-lock.json`\r\nthat should **not** be removed, or you will have to re-install Linny-R.\r\nIt should also contain the launch script.  On a macOS machine, this will be\r\nthe shell script `linny-r.command`, on a Windows machine the batch script\r\n`linny-r.bat`.\r\n\r\nAll other software is contained in the `node_modules` directory. It comprises\r\ntwo Node.js packages: `@xlmdom` and `linny-r`. \r\n\r\nThe `linny-r` package directory should contain this file `README.md`, the files\r\n`server.js` and `console.js` that will be run by Node.js, and the sub-directory\r\n`static`. This `static` directory should contain two HTML files: \r\n\r\n* `index.html` (the browser-based GUI) \r\n* `show-diff.html` (to display differences between two Linny-R models)\r\n\r\nIt should also contain the style sheet `linny-r.css` required by the GUI.\r\n\r\nThe sub-directories of `static` contain files that are served to the browser\r\nby the script `server.js` when it is running in Node.js.\r\n\r\n## Troubleshooting problems\r\n\r\nIf during any of the steps above you encounter problems, please try to\r\ndiagnose them and resolve them yourself. You can find a lot of useful\r\ninformation on the Linny-R user documentation website:\r\n<a href=\"https://linny-r.info\" target=\"_blank\">https://linny-r.info</a>.\r\n\r\n> [!IMPORTANT]\r\n> To diagnose a problem, always look in the CLI box where Node.js is running, \r\n> as informative server-side error messages will appear there. Scroll up to\r\n> the line where you typed the launch command to check for warnings and\r\n> messages relating to the solver.\r\n\r\nThen also look at the console window of your browser. \r\nMost browsers offer a _Web Developer Tools_ option via their application menu.\r\nThis will allow you to view the browser console, which will display JavaScript\r\nerrors in red font.\r\n\r\nIf you've tried hard, but failed, you can try to contact Pieter Bots at\r\n``p.w.g.bots@tudelft.nl``\r\n","readmeFilename":"README.md"}