Add a top portfolio
Generate a portfolio of solutions for a conservation planning
problem() by finding a pre-specified number of solutions that
are closest to optimality (i.e the top solutions).
add_top_portfolio(x, number_solutions)
x |
|
number_solutions |
|
This strategy for generating a portfolio requires problems to
be solved using the Gurobi software suite (i.e. using
add_gurobi_solver(). Specifically, version 9.0.0 (or greater)
of the gurobi package must be installed.
Note that the number of solutions returned may be less than the argument to
number_solutions, if the total number of feasible solutions
is less than the number of solutions requested.
Object (i.e. ConservationProblem) with the portfolio
added to it.
## Not run:
# set seed for reproducibility
set.seed(600)
# load data
data(sim_pu_raster, sim_features)
# create minimal problem with a portfolio for the top 5 solutions
p1 <- problem(sim_pu_raster, sim_features) %>%
add_min_set_objective() %>%
add_relative_targets(0.05) %>%
add_top_portfolio(number_solutions = 5) %>%
add_default_solver(gap = 0, verbose = FALSE)
# solve problem and generate portfolio
s1 <- solve(p1)
# print number of solutions found
print(length(s1))
# plot solutions
plot(stack(s1), axes = FALSE, box = FALSE)
# create multi-zone problem with a portfolio for the top 5 solutions
p2 <- problem(sim_pu_zones_stack, sim_features_zones) %>%
add_min_set_objective() %>%
add_relative_targets(matrix(runif(15, 0.1, 0.2), nrow = 5,
ncol = 3)) %>%
add_top_portfolio(number_solutions = 5) %>%
add_default_solver(gap = 0, verbose = FALSE)
# solve problem and generate portfolio
s2 <- solve(p2)
# print number of solutions found
print(length(s2))
# plot solutions in portfolio
plot(stack(lapply(s2, category_layer)), main = "solution", axes = FALSE,
box = FALSE)
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