Package: multiscape 1.1.2

multiscape: Multi-Objective Spatial Planning

Provides a modular framework for exact multi-objective spatial planning using mixed-integer programming. The package supports the definition of planning problems through planning units, features, management actions, action effects, spatial relations, targets, constraints, and objective functions. It enables the optimisation of spatial planning portfolios under considerations such as boundary structure, connectivity, and fragmentation. Supported multi-objective methods include weighted-sum aggregation, epsilon-constraint, and the augmented epsilon-constraint method. Problems can be solved with several commercial and open-source optimisation solvers. Optional solver backends include the 'gurobi' R package, which is distributed with the Gurobi Optimizer installation <https://docs.gurobi.com/projects/optimizer/en/13.0/reference/r/setup.html>, and the 'rcbc' R package, available from GitHub at <https://github.com/dirkschumacher/rcbc>. For background on multi-objective optimisation methods, see Halffmann et al. (2022) <doi:10.1002/mcda.1780>; for the augmented epsilon-constraint method, see Mavrotas (2009) <doi:10.1016/j.amc.2009.03.037>.

Authors:José Salgado-Rojas [aut, cre], Matías Moreno-Faguett [aut], Núria Aquilué [aut]

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manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
multiscape/json (API)

# Install 'multiscape' in R:
install.packages('multiscape', repos = c('https://josesalgr.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/josesalgr/multiscape/issues

Pkgdown/docs site:https://josesalgr.github.io

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

cpp

3.93 score 1 stars 5 scripts 446 downloads 68 exports 53 dependencies

Last updated from:91b989fedb. Checks:12 OK, 1 FAIL. Indexed: yes.

TargetResultTimeFilesSyslog
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linux-devel-x86_64OK388
source / vignettesOK394
linux-release-arm64OK366
linux-release-x86_64OK393
macos-release-arm64OK271
macos-release-x86_64OK759
macos-oldrel-arm64OK320
macos-oldrel-x86_64OK428
windows-develOK474
windows-releaseOK507
windows-oldrelOK455
wasm-releaseFAIL204

Exports:%>%add_actionsadd_benefitsadd_constraint_areaadd_constraint_budgetadd_constraint_locked_actionsadd_constraint_locked_planning_unitsadd_constraint_locked_puadd_constraint_targets_absoluteadd_constraint_targets_relativeadd_effectsadd_lossesadd_objective_max_benefitadd_objective_max_net_profitadd_objective_max_profitadd_objective_min_costadd_objective_min_fragmentation_actionadd_objective_min_fragmentation_planning_unitsadd_objective_min_fragmentation_puadd_objective_min_intervention_impactadd_objective_min_lossadd_profitadd_spatial_boundaryadd_spatial_distanceadd_spatial_knnadd_spatial_queenadd_spatial_relationsadd_spatial_rookcompile_modelcreate_problemfrontier_distancesfrontier_extremesfrontier_kneeget_actionsget_featuresget_objectivesget_planning_unitsget_puget_runsget_targetsload_sim_features_rastermo_controlplot_spatial_actionsplot_spatial_featuresplot_spatial_planning_unitsplot_spatial_puplot_tradeoffProblemrun_gridrun_manualselection_frequencyselection_similarityset_method_augmeconset_method_epsilon_constraintset_method_weighted_sumset_runs_controlset_runs_gridset_runs_manualset_solverset_solver_cbcset_solver_cplexset_solver_gurobiset_solver_symphonysolution_appendsolution_filtersolution_uniqueSolutionSetsolve

Dependencies:assertthatBHclassclassIntclicpp11DBIdplyre1071exactextractrfarvergenericsggplot2ggrepelgluegtableisobandKernSmoothlabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmoocorepillarpkgconfigprotoproxyR6RANNrasterrbibutilsRColorBrewerRcppRcppArmadilloRdpackrlangs2S7scalessfspterratibbletidyselectunitsutf8vctrsviridisLitewithrwk

Readme and manuals

Help Manual

Help pageTopics
Add management actions to a planning problemadd_actions
Add benefitsadd_benefits
Add area constraintadd_constraint_area
Add budget constraintadd_constraint_budget
Add locked action decisions to a planning problemadd_constraint_locked_actions
Add locked planning units to a problemadd_constraint_locked_planning_units
Add locked planning units to a problemadd_constraint_locked_pu
Add absolute targetsadd_constraint_targets_absolute
Add relative targetsadd_constraint_targets_relative
Add action effects to a planning problemadd_effects
Add lossesadd_losses
Add objective: maximize benefitadd_objective_max_benefit
Add objective: maximize net profitadd_objective_max_net_profit
Add objective: maximize profitadd_objective_max_profit
Add objective: minimize costadd_objective_min_cost
Add objective: minimize action fragmentationadd_objective_min_fragmentation_action
Add objective: minimize planning-unit fragmentationadd_objective_min_fragmentation_planning_units
Add objective: minimize planning-unit fragmentationadd_objective_min_fragmentation_pu
Add objective: minimize intervention impactadd_objective_min_intervention_impact
Add objective: minimize lossadd_objective_min_loss
Add profit to a planning problemadd_profit
Add spatial boundary-length relationsadd_spatial_boundary
Add distance-threshold spatial relationsadd_spatial_distance
Add k-nearest-neighbours spatial relationsadd_spatial_knn
Add queen adjacency from polygonsadd_spatial_queen
Add spatial relationsadd_spatial_relations
Add rook adjacency from polygonsadd_spatial_rook
Compile the optimization model stored in a Problemcompile_model compile_model.Problem
Create a planning problem input objectcreate_problem create_problem,ANY,ANY,missing-method create_problem,ANY,ANY,NULL-method create_problem,ANY,data.frame,data.frame-method create_problem,data.frame,data.frame,data.frame-method
Compute distances to observed ideal or nadir pointsfrontier_distances
Find objective-wise extreme solutionsfrontier_extremes
Identify knee solutions on an observed Pareto frontierfrontier_knee
Get action results from a solution setget_actions
Get feature summary from a solution setget_features
Get objective values from a solution setget_objectives
Get planning-unit results from a solution setget_planning_units
Get planning-unit results from a solution setget_pu
Get run-level metadata from a solution setget_runs
Get target achievement summary from a solution setget_targets
Example feature rasterload_sim_features_raster
Control multi-objective run behaviormo_control
Plot selected actions in spaceplot_spatial_actions
Plot spatial feature values from a solution setplot_spatial_features
Plot selected planning units in spaceplot_spatial_planning_units
Plot selected planning units in spaceplot_spatial_pu
Plot trade-offs from a solution setplot_tradeoff
Problem classProblem problem-class
Define an automatic multi-objective run gridrun_grid
Define a manual multi-objective run designrun_manual
Calculate selection frequency across solutionsselection_frequency
Calculate structural similarity among solutionsselection_similarity
Set the AUGMECON multi-objective methodset_method_augmecon
Set the epsilon-constraint multi-objective methodset_method_epsilon_constraint
Set the weighted-sum multi-objective methodset_method_weighted_sum
Control multi-objective run behaviorset_runs_control
Define an automatic multi-objective run gridset_runs_grid
Define a manual multi-objective run designset_runs_manual
Configure solver settingsset_solver
Configure CPLEX solver settingsset_solver_cbc
Configure CPLEX solver settingsset_solver_cplex
Configure Gurobi solver settingsset_solver_gurobi
Configure SYMPHONY solver settingsset_solver_symphony
Simulated feature distributionsim_dist_features
Simulated featuressim_features
Simulated planning unitssim_pu
Simulated planning unitssim_pu_sf
Append solutions from another solution setsolution_append
Filter solutions in a solution setsolution_filter
Keep unique solutions in a solution setsolution_unique
SolutionSet classSolutionSet solutionset-class
Solve a planning problemsolve solve.Problem