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prioriactions  

Multi-Action Conservation Planning
View on CRAN: Click here


Download and install prioriactions package within the R console
Install from CRAN:
install.packages("prioriactions")

Install from Github:
library("remotes")
install_github("cran/prioriactions")

Install by package version:
library("remotes")
install_version("prioriactions", "0.5.0")



Attach the package and use:
library("prioriactions")
Maintained by
Jose Salgado-Rojas
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-12-15
Latest Update: 2023-08-13
Description:
This uses a mixed integer mathematical programming (MIP) approach for building and solving multi-action planning problems, where the goal is to find an optimal combination of management actions that abate threats, in an efficient way while accounting for spatial aspects. Thus, optimizing the connectivity and conservation effectiveness of the prioritized units and of the deployed actions. The package is capable of handling different commercial (gurobi, CPLEX) and non-commercial (symphony, CBC) MIP solvers. Gurobi optimization solver can be installed using comprehensive instructions in the 'gurobi' installation vignette of the prioritizr package (available in ). Instead, 'CPLEX' optimization solver can be obtain from IBM CPLEX web page (available here ). Additionally, the 'rcbc' R package (available at ) can be used to obtain solutions using the CBC optimization software (). Methods used in the package refers to Salgado-Rojas et al. (2020) , Beyer et al. (2016) , Cattarino et al. (2015) and Watts et al. (2009) . See the prioriactions website for more information, documentations and examples.
How to cite:
Jose Salgado-Rojas (2021). prioriactions: Multi-Action Conservation Planning. R package version 0.5.0, https://cran.r-project.org/web/packages/prioriactions. Accessed 21 Nov. 2024.
Previous versions and publish date:
0.3.2 (2021-12-15 09:20), 0.3.3 (2022-01-14 12:52), 0.4.1 (2022-08-16 15:30), 0.4.2 (2023-03-23 00:20), 0.4 (2022-02-09 23:30)
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