add_mandatory_allocation_constraints: Add mandatory allocation constraints

add_mandatory_allocation_constraintsR Documentation

Add mandatory allocation constraints

Description

Add constraints to ensure that every planning unit is allocated to a management zone in the solution. Note that this function can only be used with problems that contain multiple zones.

Usage

## S4 method for signature 'ConservationProblem'
add_mandatory_allocation_constraints(x)

Arguments

x

problem() (i.e., ConservationProblem) object.

Details

For a conservation planning problem() with multiple management zones, it may sometimes be desirable to obtain a solution that assigns each and every single planning unit to a zone. For example, when developing land-use plans, some decision makers may require that each and every single parcel of land has been allocated a specific land-use type. In other words are no "left over" areas. Although it might seem tempting to simply solve the problem and manually assign "left over" planning units to a default zone afterwards (e.g., an "other", "urban", or "grazing" land-use), this could result in highly sub-optimal solutions if there penalties for siting the default land-use adjacent to other zones. Instead, this function can be used to specify that all planning units in a problem with multiple zones must be allocated to a management zone (i.e., zone allocation is mandatory).

Value

Object (i.e., ConservationProblem) with the constraints added to it.

See Also

See constraints for an overview of all functions for adding constraints.

Other constraints: add_contiguity_constraints(), add_feature_contiguity_constraints(), add_linear_constraints(), add_locked_in_constraints(), add_locked_out_constraints(), add_manual_bounded_constraints(), add_manual_locked_constraints(), add_neighbor_constraints()

Examples

# set seed for reproducibility
set.seed(500)

# load data
data(sim_pu_zones_stack, sim_features_zones)

# create multi-zone problem with minimum set objective
targets_matrix <- matrix(rpois(15, 1), nrow = 5, ncol = 3)

# create minimal problem with minimum set objective
p1 <- problem(sim_pu_zones_stack, sim_features_zones) %>%
      add_min_set_objective() %>%
      add_absolute_targets(targets_matrix) %>%
      add_binary_decisions() %>%
      add_default_solver(verbose = FALSE)

# create another problem that is the same as p1, but has constraints
# to mandate that every planning unit in the solution is assigned to
# zone
p2 <- p1 %>% add_mandatory_allocation_constraints()
## Not run: 
# solve problems
s1 <- solve(p1)
s2 <- solve(p2)

# convert solutions into category layers, where each pixel is assigned
 # value indicating which zone it was assigned to in the zone
c1 <- category_layer(s1)
c2 <- category_layer(s2)

# plot solution category layers
plot(stack(c1, c2), main = c("default", "mandatory allocation"),
     axes = FALSE, box = FALSE)

## End(Not run)

prioritizr documentation built on Sept. 18, 2022, 1:05 a.m.