Package: optimLanduse 1.2.1
optimLanduse: Robust Land-Use Optimization
Robust multi-criteria land-allocation optimization that explicitly accounts for the uncertainty of the indicators in the objective function. Solves the problem of allocating scarce land to various land-use options with regard to multiple, coequal indicators. The method aims to find the land allocation that represents the indicator composition with the best possible trade-off under uncertainty. optimLanduse includes the actual optimization procedure as described by Knoke et al. (2016) <doi:10.1038/ncomms11877> and the post-hoc calculation of the portfolio performance as presented by Gosling et al. (2020) <doi:10.1016/j.jenvman.2020.110248>.
Authors:
optimLanduse_1.2.1.tar.gz
optimLanduse_1.2.1.zip(r-4.5)optimLanduse_1.2.1.zip(r-4.4)optimLanduse_1.2.1.zip(r-4.3)
optimLanduse_1.2.1.tgz(r-4.4-any)optimLanduse_1.2.1.tgz(r-4.3-any)
optimLanduse_1.2.1.tar.gz(r-4.5-noble)optimLanduse_1.2.1.tar.gz(r-4.4-noble)
optimLanduse_1.2.1.tgz(r-4.4-emscripten)optimLanduse_1.2.1.tgz(r-4.3-emscripten)
optimLanduse.pdf |optimLanduse.html✨
optimLanduse/json (API)
NEWS
# Install 'optimLanduse' in R: |
install.packages('optimLanduse', repos = c('https://forest-economics-goettingen.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/forest-economics-goettingen/optimlanduse/issues
Last updated 9 months agofrom:57c9a2a910. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 11 2024 |
R-4.5-win | OK | Nov 11 2024 |
R-4.5-linux | OK | Nov 11 2024 |
R-4.4-win | OK | Nov 11 2024 |
R-4.4-mac | OK | Nov 11 2024 |
R-4.3-win | OK | Nov 11 2024 |
R-4.3-mac | OK | Nov 11 2024 |
Exports:autoSearchcalcPerformancedataPreparationexampleDatainitScenariosolveScenario
Dependencies:clicodetoolscpp11digestdplyrfansifuturefuture.applygenericsglobalsgluelifecyclelistenvlpSolveAPImagrittrparallellypillarpkgconfigpurrrR6rlangstringistringrtibbletidyrtidyselectutf8vctrswithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Optimize all possible indicator combinations | autoSearch |
Attach portfolio performance and distance to target | calcPerformance |
Transform data into the expected format | dataPreparation |
Exemplary data in the required format | exampleData |
Initialize the robust optimization | initScenario |
Perform the optimization | solveScenario |