prioritizr: add_cuts_portfolio – R documentation

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add_cuts_portfolio

Add Bender's cuts portfolio

Description

Generate a portfolio of solutions for a conservation planning problem() using Bender's cuts (discussed in Rodrigues et al. 2000). This is recommended as a replacement for add_gap_portfolio() when the Gurobi software is not available.

Usage

add_cuts_portfolio(x, number_solutions = 10L)

Arguments

`x`	`problem()` (i.e. `ConservationProblem`) object.
`number_solutions`	`integer` number of attempts to generate different solutions. Defaults to 10.

Details

This strategy for generating a portfolio of solutions involves solving the problem multiple times and adding additional constraints to forbid previously obtained solutions. In general, this strategy is most useful when problems take a long time to solve and benefit from having multiple threads allocated for solving an individual problem.

Value

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

Notes

In early versions (< 4.0.1), this function was only compatible with Gurobi (i.e. add_gurobi_solver()). To provide functionality with exact algorithm solvers, this function now adds constraints to the problem formulation to generate multiple solutions.

References

Rodrigues AS, Cerdeira OJ, and Gaston KJ (2000) Flexibility, efficiency, and accountability: adapting reserve selection algorithms to more complex conservation problems. Ecography, 23: 565–574.

Examples

# set seed for reproducibility
set.seed(500)

# load data
data(sim_pu_raster, sim_features, sim_pu_zones_stack, sim_features_zones)

# create minimal problem with cuts portfolio
p1 <- problem(sim_pu_raster, sim_features) %>%
      add_min_set_objective() %>%
      add_relative_targets(0.2) %>%
      add_cuts_portfolio(10) %>%
      add_default_solver(gap = 0.2, verbose = FALSE)

## Not run: 
# solve problem and generate 10 solutions within 20% of optimality
s1 <- solve(p1)

# plot solutions in portfolio
plot(stack(s1), axes = FALSE, box = FALSE)

## End(Not run)
# build multi-zone conservation problem with cuts portfolio
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_binary_decisions() %>%
      add_cuts_portfolio(10) %>%
      add_default_solver(gap = 0.2, verbose = FALSE)

## Not run: 
# solve the problem
s2 <- solve(p2)

# print solution
str(s2, max.level = 1)

# plot solutions in portfolio
plot(stack(lapply(s2, category_layer)), main = "solution", axes = FALSE,
     box = FALSE)

## End(Not run)

prioritizr

Systematic Conservation Prioritization in R

v7.0.1

GPL-3

Authors

Jeffrey O Hanson [aut] (<https://orcid.org/0000-0002-4716-6134>), Richard Schuster [aut, cre] (<https://orcid.org/0000-0003-3191-7869>), Nina Morrell [aut], Matthew Strimas-Mackey [aut] (<https://orcid.org/0000-0001-8929-7776>), Matthew E Watts [aut], Peter Arcese [aut] (<https://orcid.org/0000-0002-8097-482X>), Joseph Bennett [aut] (<https://orcid.org/0000-0002-3901-9513>), Hugh P Possingham [aut] (<https://orcid.org/0000-0001-7755-996X>)

Initial release