Multi-Action, Multi-Objective Spatial Planning


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Documentation for package ‘multiscape’ version 1.4.2

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add_actions Add management actions to a planning problem
add_action_sets Register sets of management actions
add_benefits Add benefits
add_constraint_action_cardinality Constrain the number of actions selected per planning unit
add_constraint_action_excludes Make actions mutually exclusive within each planning unit
add_constraint_action_requires Require companion actions in each planning unit
add_constraint_action_together Select actions together within each planning unit
add_constraint_area Add area constraint
add_constraint_budget Add budget constraint
add_constraint_locked_actions Add locked action decisions to a planning problem
add_constraint_locked_planning_units Add locked planning units to a problem
add_constraint_locked_pu Add locked planning units to a problem
add_constraint_targets_absolute Add absolute targets
add_constraint_targets_relative Add relative targets
add_effects Add action effects to a planning problem
add_losses Add losses
add_objective_max_benefit Deprecated benefit objective
add_objective_max_effect Add objective: maximize signed effect
add_objective_max_net_profit Add objective: maximize net profit
add_objective_max_profit Add objective: maximize profit
add_objective_min_cost Add objective: minimize cost
add_objective_min_effect Add objective: minimise signed effect
add_objective_min_fragmentation_action Add objective: minimise action fragmentation
add_objective_min_fragmentation_planning_units Add objective: minimise planning-unit fragmentation
add_objective_min_fragmentation_pu Add objective: minimize planning-unit fragmentation
add_objective_min_intervention_impact Add objective: minimize intervention impact
add_objective_min_loss Deprecated objective: minimize loss
add_profit Add profit to a planning problem
add_spatial_boundary Add spatial boundary-length relations
add_spatial_distance Add distance-threshold spatial relations
add_spatial_knn Add k-nearest-neighbours spatial relations
add_spatial_queen Add queen adjacency from polygons
add_spatial_relations Add spatial relations
add_spatial_rook Add rook adjacency from polygons
compile_model Compile the optimization model stored in a Problem
compile_model.Problem Compile the optimization model stored in a Problem
create_problem Create a planning problem input object
create_problem-method Create a planning problem input object
frontier_distances Compute distances to observed ideal or nadir points
frontier_extremes Find objective-wise extreme solutions
frontier_knee Identify knee solutions on an observed Pareto frontier
frontier_neighbors Identify neighboring solutions in objective space
get_actions Get action results from a solution set
get_action_sets Inspect registered action sets
get_features Get feature summary from a solution set
get_objectives Get objective values from a solution set
get_planning_units Get planning-unit results from a solution set
get_pu Get planning-unit results from a solution set
get_runs Get run-level metadata from a solution set
get_solution_states Get planning-unit states from stored solutions
get_targets Get target achievement summary from a solution set
linkage_contrasts Select informative solution contrasts
linkage_distances Compare objective and decision distances
linkage_transition Describe the transition between two solutions
linkage_turnover Measure decision turnover along an objective-space neighborhood
load_ecosystem_services Load the ecosystem-services spatial example
load_meseta Load the Meseta Iberica spatial action example
load_sim_features_raster Example feature raster
load_sim_multiaction Load the simulated spatial multi-action example
mo_control Control multi-objective run behavior
plot_spatial_actions Plot selected actions in space
plot_spatial_features Plot spatial feature values from a solution set
plot_spatial_planning_units Plot selected planning units in space
plot_spatial_pu Plot selected planning units in space
plot_tradeoff Plot trade-offs from a solution set
Problem Problem class
problem-class Problem class
run_grid Define an automatic multi-objective run grid
run_manual Define a manual multi-objective run design
selection_consistency Summarize consistency of planning-unit states
selection_frequency Calculate selection frequency across solutions
selection_similarity Calculate structural similarity among solutions
set_method_augmecon Configure the augmented epsilon-constraint method (AUGMECON)
set_method_epsilon_constraint Configure the epsilon-constraint multi-objective method
set_method_weighted_sum Configure the weighted-sum multi-objective method
set_runs_control Control multi-objective run behavior
set_runs_grid Define an automatic multi-objective run grid
set_runs_manual Define a manual multi-objective run design
set_solver Configure solver settings
set_solver_cbc Configure CBC solver settings
set_solver_cplex Configure CPLEX solver settings
set_solver_gurobi Configure Gurobi solver settings
set_solver_symphony Configure SYMPHONY solver settings
sim_dist_features Simulated feature distribution
sim_features Simulated features
sim_multiaction Simulated spatial multi-action planning inputs
sim_pu Simulated planning units
sim_pu_sf Simulated planning units
SolutionSet SolutionSet class
solutionset-class SolutionSet class
solution_append Append solutions from another solution set
solution_filter Filter solutions in a solution set
solution_unique Keep unique solutions in a solution set
solve Solve a planning problem
solve.Problem Solve a planning problem