prioritizr (version 4.1.5)

decisions: Specify the type of decisions

Description

Conservation planning problems involve making decisions on how different planning units will be managed. These decisions might involve turning an entire planning unit into a protected area, turning part of a planning unit into a protected area, or allocating a planning unit to a specific management zone. If no decision is explicitly added to a problem, then binary decisions will be used by default.

Details

Only a single type of decision can be added to a conservation planning problem.If multiple decisions are added to problem, then the last one to be added will be used.

The following decisions can be added to a conservation planning problem:

add_binary_decisions

Add a binary decision to a conservation planning problem. This is the classic decision of either prioritizing or not prioritizing a planning unit. Typically, this decision has the assumed action of buying the planning unit to include in a protected area network. If no decision is added to a problem object then this decision class will be used by default.

add_proportion_decisions

Add a proportion decision to a conservation planning problem. This is a relaxed decision where a part of a planning unit can be prioritized, as opposed to the default of the entire planning unit. Typically, this decision has the assumed action of buying a fraction of a planning unit to include in a protected area network.

add_semicontinuous_decisions

Add a semi-continuous decision to a conservation planning problem. This decision is similar to add_proportion_decision except that it has an upper bound parameter. By default, the decision can range from prioritizing none (0 %) to all (100 %) of a planning unit. However, a upper bound can be specified to ensure that at most only a fraction (e.g. 80 %) of a planning unit can be preserved. This type of decision may be useful when it is not practical to conserve the entire area encompassed by any single planning unit.

See Also

constraints, objectives, penalties, portfolios, problem, solvers, targets.

Examples

# NOT RUN {
# load data
data(sim_pu_raster, sim_features)

# create basic problem and using the default decision types (binary)
p1 <- problem(sim_pu_raster, sim_features) %>%
      add_min_set_objective() %>%
      add_relative_targets(0.1)

# create problem with manually specified binary decisions
p2 <- p1 %>% add_binary_decisions()

# create problem with proportion decisions
p3 <- p1 %>% add_proportion_decisions()

# create problem with semicontinuous decisions
p4 <- p1 %>% add_semicontinuous_decisions(upper_limit = 0.5)

# }
# NOT RUN {
# solve problem
s <- stack(solve(p1), solve(p2), solve(p3), solve(p4))

# plot solutions
plot(s, main = c("default (binary)", "binary", "proportion",
                 "semicontinuous (upper = 0.5)"))
# }
# NOT RUN {
# }