The code is is derived from the Robot Dance project tayored to analyze vaccine deployment.
You can use it to reproduce the experiments in the companion manuscript.
This code is written in Julia and
Python, so you need both installed. To install Julia you should
go to its website, select download and follow instructions. After installing Julia you need
to use its package manager and install the JuMP and Ipopt packages.
To get good performance out of Ipopt, it is very important to use a high performance linear
solver. The default free solver, mumps works well for 10 cities or so. If you want to
solve larger problems with tens of cities you will need to compile Ipopt with support to
HSL linear solvers. Robot dance uses MA97 in the code whenever
available. I have also prepared a little document describing how to
compile Ipopt with HSL under Ubuntu.
There are many ways to install Python. I use
Anaconda. By installing Anaconda you get a
comprehensive and updated Python environment with packages the code use like numpy,
scipy , and matplotlib.
After that install PyJulia.
Different experiments are made using different notebooks. If you need assistence, get in touch.
The code uses a highly parallel optimization solver to run a large scale optimization problem, named Ipopt, which is installed as a Julia package. This demands a good computer. A problem with more than 10-20 cities/regions the solver may face difficulties and stall. In order to avoid this you may need to install Ipopt with HSL. HSL is free for research. Please look at these instructions of how to compile Ipopt if needed. Also long time horizons (like the 400 days simulations we did in he report) are very demanding. The code is not ready to run on a cluster. We will try to continuously improve the code in order to overcome these limitations.
Copyright Paulo J. S. Silva, Luis Gustavo Nonato, and Marcelo Córdova. See the license file.
This research is supported by CeMEAI/FAPESP, Instituto Serrapilheira, and CNPq.
We provide this code hoping that it will be useful for others. Please if you use it, let us know about you experiences. Moreover, if you use this code in any publication, please cite us. This is very important. For the moment we only have the manuscript, so cite it as
Nonato, L. G; Peixoto, P.; Pereira, T.; Sagastizabal, C.; Silva, P. J. S. "Robot Dance: a mathematical optimization platform for intervention against Covid-19 in a complex network". Optimization Online, 2020.