prioritizr - Systematic Conservation Prioritization in R
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
constructed to optimize the spatial allocation of different
management actions or zones, meaning that conservation
practitioners can identify solutions that benefit multiple
stakeholders. To solve large-scale or complex conservation
planning problems, users should install the Gurobi optimization
software (available from <https://www.gurobi.com/>) and the
'gurobi' R package (see Gurobi Installation Guide vignette for
details). Users can also install the IBM CPLEX software
(<https://www.ibm.com/products/ilog-cplex-optimization-studio/cplex-optimizer>)
and the 'cplexAPI' R package (available at
<https://github.com/cran/cplexAPI>). Additionally, the 'rcbc' R
package (available at <https://github.com/dirkschumacher/rcbc>)
can be used to generate solutions using the CBC optimization
software (<https://github.com/coin-or/Cbc>). For further
details, see Hanson et al. (2025) <doi:10.1111/cobi.14376>.
