Jeffrey Hanson
Matt Strimas-Mackey
Description: Systematic conservation prioritization using mixed integer linear programming (MILP). It provides a flexible interface for building and solving conservation planning problems. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. By using exact algorithm solvers, solutions can be generated that are guaranteed to be optimal (or within a pre-specified optimality gap). Furthermore, conservation problems can be con
The prioritizr R package uses mixed integer linear programming (MILP) techniques to provide a flexible interface for building and solving conservation planning problems. It supports a broad range of objectives, constraints, and penalties that can be used to custom-tailor conservation planning problems to the specific needs of a conservation planning exercise. Once built, conservation planning problems can be solved using a variety of commercial and open-source exact algorithm solvers. In contrast to the alg
The latest official version of the prioritizr R package can be installed from the Comprehensive R Archive Network (CRAN) using the following R code.
install.packages ( "prioritizr" , repos = "https://cran.rstudio.com/" ) Alternatively, the latest development version can be installed from GitHub using the following code. Please note that while developmental versions may contain additional features not present in the official version, they may also contain coding errors.
Jeffrey Hanson
Matt Strimas-Mackey