Multi-Action Conservation Planning
This project was financed by the National Agency of Research and Development, ANID, Chile, through the grant FONDECYT N.1180670 and through the Complex Engineering Systems Institute PIA/BASAL AFB180003. Also it has received funding from the European Union’s H2020 research and innovation program under the Marie Sklodowska-Curie grant agreement N.691149 (SuFoRun).
Overview
The prioriactions
package allows you to create and solve conservation
planning problems that involve multiple threats and actions. This uses
techniques of integer linear programming (ILP), obtaining optimal
solutions or with a certain degree of guaranteed quality (gap). Due to
its flexibility, the package offers the possibility of creating
different mathematical models with multiple requirements (spatial,
budget requirements, etc.). All the included models are presented in
detail in Salgado-Rojas et al. (2020). The package has a variety of
commercial and open-source exact algorithm solvers that guarantee to
find optimal solutions.
Installation
Package prioriactions
can be found at CRAN, where it is updated every
few months. Installation from CRAN can be done via:
install.packages("prioriactions")
Also, the latest development version of prioriactions
can be installed
from GitHub using the
following code (If you are using Windows, it is necessary to install
Rtools beforehand).
if (!require(remotes)) install.packages("remotes")
remotes::install_github("prioriactions/prioriactions")
Usage
You can browse the package documentation online at https://prioriactions.github.io/prioriactions/.
If this is your first time using prioriactions
, we strongly recommend
reading the Introduction to
prioriactions
vignette.
If you believe you’ve found a bug in prioriactions
, please file a bug
(and, if possible, a reproducible
example) at
https://github.com/prioriactions/prioriactions/issues.
References
- Salgado-Rojas J, Alvarez-Miranda E, Hermoso V, Garcia-Gonzalo J, Weintraub A. A mixed integer programming approach for multi-action planning for threat management. Ecological Modelling 2020; 418:108901. DOI: https://doi.org/10.1016/j.ecolmodel.2019.108901.