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.

# S4 method for ConservationProblem
add_mandatory_allocation_constraints(x)

Arguments

x

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

Value

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

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).

See also

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() # \dontrun{ # solve problems s1 <- solve(p1)
#> $LogToConsole #> [1] 0 #> #> $LogFile #> [1] "" #> #> $Presolve #> [1] 2 #> #> $MIPGap #> [1] 0.1 #> #> $TimeLimit #> [1] 2147483647 #> #> $Threads #> [1] 1 #> #> $NumericFocus #> [1] 0 #>
s2 <- solve(p2)
#> $LogToConsole #> [1] 0 #> #> $LogFile #> [1] "" #> #> $Presolve #> [1] 2 #> #> $MIPGap #> [1] 0.1 #> #> $TimeLimit #> [1] 2147483647 #> #> $Threads #> [1] 1 #> #> $NumericFocus #> [1] 0 #>
# 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)
# }