MMVD: a robot controlled warehouse simulator
This application is a real-life example of operational research algorithms implementation.
A warehouse with robots looks like this.
There's a number of challenges we have to face when we want to optimize the workflow in such warehouse.
- Pathfinding (robots should reach shelves in an optimal way, for example: cost and time efficient).
- Managing a fleet of devices (which robots go to charging station, which robots pick up specific shelves, etc).
- Specifying an appearance order for shelves.
This example can be far more advanced, and implementation specific.
(Optional) Make a virtual environment and activate it:
$ virtualenv MMVD_venv $ source MMVD_venv/bin/activate
Clone this repository:
$ cd MMVD_venv $ git clone https://github.com/WojciechFocus/MMVD.git $ cd MMVD
Install this application:
$ python setup.py install
It should now be installed.
For more advanced installation instructions please follow :ref:`installation_long`.
Follow :ref:`installation` but in point 3. invoke this command:
$ pip install -e .
After installing the package,
MMVD.py executable should become available
in your system:
$ MMVD.py --help Usage: MMVD.py [OPTIONS] WAREHOUSE ROBOTS ORDER Start application and load specific warehouse map from WAREHOUSE, load initial robots positions from ROBOTS. Finally load products order from ORDER. All paths must point to readable, existing files. Options: --gantt / --no-gantt whether or not to generate Gantt chart to visualize handling order by robots --gui / --no-gui whether or not to visualize robot movements in Tk GUI --summary / --no-summary whether or not to show best solution --tabu-rounds INTEGER number of Tabu iterations --tabu-memory INTEGER number of Tabu items held in short-term memory --verbose / --no-verbose how loud should the program output be --help Show this message and exit.