User Guide
Introduction
The Operations Research Tool is designed for solving optimization problems such as Linear Programming (LP) and Mixed Integer Programming (MIP). This guide will walk you through how to use the tool, from installation to solving problems and exporting results.
Table of Contents
Installation/Access
Online
You can always access the Tool without any installation on our GitHub Pages instance.
Local
Install dependencies
This project relies on NextJs. Please follow its installation instructions to get everything ready.
Clone the repository
Using Git:
git clone https://github.com/Spaceholder-Programming/Operations-Research-Tool.git
Building the site
Navigate towards the folder, where the project is located on your machine via terminal. Afterwards, execute the following command:
npm build
Run
npm start
Access the Tool using your browser:
You can access the tool via browser on your machine. The default port is 3000.
If you can not reach the tool under this link, the default port is blocked and you have to check the terminal to get the correct port.
After Installation
The following sections will give an in depth guide on how to use the tool.
Select Language
You can change the language of the tool by selecting the language from the dropdown menu. Currently supported languages are:
- English
- German
Input Model Data
- Objective : Define the objective function you want to maximize or minimize (e.g., 3x1 + 4x2).
- Constraints : Add constraints in the format like x1 + x2 ≤ 10 or x1 ≥ 0.
- Bounds : Insert your bounds. Variables have to be greater or equal to 0.
- Variable Definitions : Specify whether variables are continuous or integer.
Solving the Problem
- Click Calculate : After entering the model, click the "Calculate" button.
- Real-time Feedback : The tool will provide real-time updates on the progress.
- View Results : Once the problem is solved, the optimal values of decision variables and the objective function will be displayed.
Export
- Exporting Problems : You can export the Problem as LP or MPS clicking the "Export as LP" or "Export as MPS" button.
Troubleshooting
Error Handling
Input Validation Errors : If there is a problem with your input (e.g., incorrectly formatted constraints or missing variables), an error message will appear indicating what needs to be fixed. Solver Errors : If the solver encounters an issue (e.g., infeasibility, unbounded solution), appropriate error messages will guide you to correct your model.
Common Issues
Problem Doesn't Solve: Ensure that all constraints and the objective function are correctly formatted.
Unrecognized Variables: Check that all variables are consistently named across the objective function and constraints.
Infeasible Solution : Review constraints to ensure that the model is solvable under the given conditions.
Issues
If you encounter further issues, refer to the Contributing section for ways to report bugs or request features.
Spaceholder-Programming 2024.