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 (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 (https://github.com/cran/cplexAPI). Additionally, the 'rcbc' R package (https://github.com/dirkschumacher/rcbc) can be used to generate solutions using the CBC optimization software (https://github.com/coin-or/Cbc).
- Version8.0.4
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- Languageen-US
- Last release06/05/2024
Documentation
Team
Richard Schuster
Matthew Strimas-Mackey
Show author detailsRolesAuthorJeffrey O Hanson
Show author detailsRolesAuthorJoseph R Bennett
Nina Morrell
Show author detailsRolesAuthorBrandon P M Edwards
Matthew E Watts
Show author detailsRolesAuthorPeter Arcese
Hugh P Possingham
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- Imports15 packages
- Suggests9 packages
- Linking To3 packages
- Reverse Imports2 packages