This repository contains code used for computing drones tours in our research work on delivery of tests.

• Python 3+
• Google OR-tools (https://developers.google.com/optimization)
• Python packages:
  • simplejson (https://github.com/simplejson/simplejson)
  • geopy (https://github.com/geopy/geopy)
  • numpy (https://numpy.org/)

Optional:

• Gurobi (https://www.gurobi.com/)
• gurobipy package for Python (https://www.gurobi.com/)

We split the problem into two separate subproblems:

• Finding the best tours to cover the whole population.
• Assigning tours to drones to minimize the maximum makespan.

We note that the tours obtained by running Google OR-tools are not optimal as they are computed by a heuristic as CVRP is NP-hard problem and its solving to optimality requires extreme computational resources.

For our computations we used geographical data stored as a list of points with "Population" property in "geojson" file (we obtained it by saving a Point Feature in QGIS software - https://qgis.org/en/site/).

One possibility is to simply make changes in prepare_data.py file to make it work with your data. Or, a json file in the following format can be used (please note that we describing here only necessary fields and structure of the file, other fields are allowed):

{
"features": [
{ "properties": { "TotBef": 111 }, "geometry": { "coordinates": [ 16.080061264303954, 58.554477805317212 ] } },
{ "properties": { "TotBef": 222 }, "geometry": { "coordinates": [ 16.090061264303954, 58.554477805317212 ] } },
]
}

Where TotBef property represents the population living in a cell centered in coordinate geometry -> coordinates.

Also please see centroids100x100.geojson as an example.

Running compute_tours.py will compute tours. There are several parameters in the top of this file which can be adjusted to select drones capacity, etc -- they all are explained in the code file itself with comments.

Running assign_tours.py will compute the optimal assignment of tours to drones which minimizes the maximum makespan. Again, there are several parameters in the top of the file, which are explained in the code comments.

The data in the file centroids100x100.geojson is obtained from the geographical data courtesy of Statistics Sweden (https://scb.se/) provided by Swedish University of Agricultural Sciences (https://www.slu.se/) under FUK (Forskning, utbildning och kulturverksamhet) license (https://www.geodata.se/anvanda/forskning-utbildning-och-kulturverksamheter/).

We publish the code under MIT license as it is the most permissible license we have managed to find and because Free Software Foundation does not recommend using informal licenses like "Do whatever you want" (https://www.gnu.org/licenses/license-list.en.html#informal).

However, our knowledge in the area of licensing is limited, therefore feel free to contact the authors if you feel that this license does not work.

Copyright 2020 https://github.com/undefiened/

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

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