Last miles project : TUM case study with World Food Program

This python code solve a revisited Inventory routing problem. A user interface is also provided. More information is available in the technical documentation or in the user guide.

Files

The Design folder contains the code that generates the interface, more precisely, the file main.py should be run to launch the interface. The interface is implemented using the python package PyQt5.

The file ISI.py is the file that contains the optimization algorithm.

The files OR_tools_solve_tsp.py and OR_tools_solve_tsp.pyprovides auxiliary functions that are used in ``ÌSI.py```.

THe file visu.py uses plotly package in order to

Guide to run the tool using python

If one have python on his computer, (or even better, having conda installed) one can run the tool using this GitHub.

The first step would be to download this repository.

Then one could launch a terminal window from the folder called Design.

An optional step here that would help would be to create a separate python environment using conda (if one have conda already installed) :

conda create envLastMile

source activate envLastMile

Then one should make sure he can use pip, the python package installer :

sudo easy_install pip

Now a second step here is to install all the packages that are needed to run the python code :

pip install numpy

pip install pandas 

pip install scipy 

pip install sklearn

pip install geopy

pip install plotly
 
pip install PuPL

pip install xlrd
  
pip install XlsxWriter
   
pip install ortools
    
pip install PyQt5

If one of those does not work, one can alternatievly use :

python -m pip install name-package

If one is using conda, one can also replace pipwith conda on any of those commands.

Then one should be able to run the tool by enterring :

python main.py

Remark : sometimes, your python app is called python3 instead, then simply run python3 main.py

Packags used in the code

Several open source python packages are needed to use the tool :

• sys
• time
• random
• copy
• numpy
• pandas
• scipy
• sklearn
• geopy
• plotly
• pulp
• XlsxWriter
• ortools
• PyQt5