NEWS.md
add_lpsolveapi_solver().gap parameter for the add_rsymphony_solver and add_lpsymphony_solver corresponded to the maximum absolute difference from the optimal objective value. This was an error due to misunderstanding the SYMPHONY documentation. Under previous versions of the package, the gap parameter actually corresponded to a relative optimality gap expressed as a percentage (such thatgap = 10 indicates that solutions must be at least 10% from optimality). We have now fixed this error and the documentation described for the gap parameter is correct. We apologize for any inconvenience this may have caused.add_rsymphony_solver and add_lpsymphony_solver functions to have a default time_limit argument set as the maximum machine integer for consistency.add_rsymphony_solver, add_lpsymphony_solver, and add_gurobi_solver functions to require logical (TRUE/FALSE) arguments for the first_feasible parameter.\dontrun instead of \donttest per CRAN policies.tibble::as.tibble with tibble::as_tibble to avoid warnings.add_heuristic_solver to skip initial step for removing projects and actions that exceed the budget. While this initial step improves solution quality, it is not conventionally used in project prioritization algorithms and so should be omitted to provide accurate benchmarks.add_max_phylo_div_objective). Specifically, 1’000 points instead of 10’000 points are now used for piece-wise linear components. It appears that reducing the precision in this manner does not affect the correctness of results, but substantially reduces the time needed to solve problems to optimality in certain situations.add_heuristic_solver algorithm so that cost-effectiveness values are calculated with projects sharing costs (e.g. if two projects share an action that costs $100, then this action contributes $50 to the cost of each project). This update makes the algorithm similar to backwards heuristics conventionally used in prioritizing species recovery projects (i.e. https://github.com/p-robot/ppp; #14).add_heuristic_solver algorithm so that it removes projects, and not actions, in an iterative fashion. This update (i) makes the algorithm comparable to the backwards heuristics conventionally used in prioritizing species recovery projects (i.e. https://github.com/p-robot/ppp) and (ii) substantially reduces run time (#14).add_heuristic_solver and add_random_solver arising from floating point comparison issue. These were causing infeasible solutions to be returned in R version 3.4.4.project_cost_effectiveness reporting incorrect costs, and cost-effectiveness values.add_heuristic_solver algorithm so that all actions and projects which exceed the budget are automatically removed prior to the iterative action removal.add_random_solver algorithms so that projects are selected instead of individual actions. This means that solutions from this solver are (i) similar to those in previous project prioritization studies and (ii) more likely to deliver better solutions (#13).replacement_costs yielding incorrect results for baseline projects when used with SYMPHONY solvers.project_cost_effectiveness function to calculate the cost-effectiveness for each conservation project in a problem.Found more than one class "tbl_df" in cache; using the first, from namespace 'tibble'” text.add_max_phylo_div_objective yielding incorrect solutions when features are ordered differently in the phylogenetic and tabular input data.solution_statistics yielding objective values for phylogenetic problems when features are ordered differently in the phylogenetic and tabular input data.return_data argument to plot_feature_persistence and plot_phylo_persistence so that plotting data can be obtained for creating custom plots.add_relative_targets and add_manual_targets (when relative targets supplied) calculations. This result in incorrect calculations.add_gurobi_solver function) now uses NumericFocus=3 to help avoid numerical issues.compile function now throws a warning if problems are likely to have numerical issues.problem. It will now throw descriptive error messages if features are missing baseline probabilities, or are associated with baseline probabilities below 1e-11.simulate_ptm_data that had a very small chance of failing due to simulating a data set where an action is not associated with any project.simulate_ppp_data and simulate_ptm_data are now sorted.