MultiConservationProblem-class: Multi-objective conservation problem class
In prioritizr: Systematic Conservation Prioritization in R
MultiConservationProblem-class R Documentation
Multi-objective conservation problem class
Description
This class is used to represent multi-objective conservation planning
problems. It stores the data (e.g., planning units, and features) and
mathematical formulation (e.g., the objective, constraints,
and other design criteria) needed to generate prioritizations.
Most users should use multi_problem() to generate new
multi-objective conservation problem objects, and the functions distributed
with the package to interact
with them (e.g., number_of_features(), number_of_planning_units()).
Only experts should use the fields and methods for this class directly.
Public fields
problemslist containing ConservationProblem objects.
defaultslist indicating if other fields contain defaults.
approachMultiObjApproach object
for specifying the multi-objective optimization approach.
solverSolver object specifying the solver for
generating solutions.
Methods
Public methods
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MultiConservationProblem$convert_total_unit_ids_to_indices()
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MultiConservationProblem$planning_unit_indices_with_finite_costs()
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MultiConservationProblem$new()
Create a new multi-objective conservation problem object.
Usage
MultiConservationProblem$new(problems)
Arguments
problemslist containing ConservationProblem objects.
Returns
A new MultiConservationProblem object.
MultiConservationProblem$summary()
Print extended information about the object.
Usage
MultiConservationProblem$summary()
Returns
Invisible TRUE.
MultiConservationProblem$print()
Print concise information about the object.
Usage
MultiConservationProblem$print()
Returns
Invisible TRUE.
MultiConservationProblem$show()
Display concise information about the object.
Usage
MultiConservationProblem$show()
Returns
Invisible TRUE.
MultiConservationProblem$repr()
Generate a character representation of the object.
Usage
MultiConservationProblem$repr()
Returns
A character value.
MultiConservationProblem$number_of_planning_units()
Obtain the number of planning units. The planning units correspond to
elements in the cost data
(e.g., indices, rows, geometries, cells) that have finite
values in at least one zone. In other words, planning unit are
elements in the cost data that do not have missing (NA) values in
every zone.
Usage
MultiConservationProblem$number_of_planning_units()
Returns
An integer value.
MultiConservationProblem$is_ids_equivalent_to_indices()
Check if planning unit identifiers are equivalent to the planning
unit indices? Only FALSE if the planning units are
data.frame format.
Usage
MultiConservationProblem$is_ids_equivalent_to_indices()
Returns
A logical value.
MultiConservationProblem$planning_unit_indices()
Obtain the planning unit indices.
Usage
MultiConservationProblem$planning_unit_indices()
Returns
An integer vector.
MultiConservationProblem$total_unit_ids()
Obtain the total unit identifiers.
Usage
MultiConservationProblem$total_unit_ids()
Returns
An integer vector.
MultiConservationProblem$convert_total_unit_ids_to_indices()
Convert total unit identifiers to indices.
Usage
MultiConservationProblem$convert_total_unit_ids_to_indices(ids)
Arguments
idsinteger vector with planning unit identifiers.
Returns
An integer vector.
MultiConservationProblem$planning_unit_indices_with_finite_costs()
Obtain the planning unit indices that are associated with
finite cost values.
Usage
MultiConservationProblem$planning_unit_indices_with_finite_costs()
Returns
A list of integer vectors. Each list element corresponds to
a different zone.
MultiConservationProblem$number_of_total_units()
Obtain the number of total units. The total units include all elements
in the cost data
(e.g., indices, rows, geometries, cells), including those with
missing (NA) values.
Usage
MultiConservationProblem$number_of_total_units()
Returns
An integer value.
MultiConservationProblem$planning_unit_class()
Get planning unit class.
Usage
MultiConservationProblem$planning_unit_class()
Returns
A character value.
MultiConservationProblem$number_of_features()
Obtain the number of features.
Usage
MultiConservationProblem$number_of_features()
Returns
An integer value.
MultiConservationProblem$feature_names()
Obtain the names of the features.
Usage
MultiConservationProblem$feature_names()
Returns
A character vector.
MultiConservationProblem$number_of_problems()
Obtain the number of problems.
Usage
MultiConservationProblem$number_of_problems()
Returns
An integer value.
MultiConservationProblem$problem_names()
Obtain the names of the problems.
Usage
MultiConservationProblem$problem_names()
Returns
A character vector.
MultiConservationProblem$number_of_zones()
Obtain the number of zones.
Usage
MultiConservationProblem$number_of_zones()
Returns
An integer value.
MultiConservationProblem$zone_names()
Obtain the zone names.
Usage
MultiConservationProblem$zone_names()
Returns
A character vector.
MultiConservationProblem$add_approach()
Create a new object with an approach added to the problem formulation.
Usage
MultiConservationProblem$add_approach(x)
Arguments
xMultiObjApproach object.
Returns
An updated MultiConservationProblem object.
MultiConservationProblem$add_solver()
Create a new object with a solver added to the problem formulation.
Usage
MultiConservationProblem$add_solver(x)
Arguments
xSolver object.
Returns
An updated MultiConservationProblem object.
MultiConservationProblem$clone()
The objects of this class are cloneable with this method.
Usage
MultiConservationProblem$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
See Also
Other classes:
ConservationModifier-class,
ConservationProblem-class,
Constraint-class,
Decision-class,
MultiObjApproach-class,
Objective-class,
OptimizationProblem-class,
Penalty-class,
Portfolio-class,
Solver-class,
Target-class,
TargetMethod-class,
Weight-class
prioritizr documentation built on Sept. 24, 2026, 5:07 p.m.
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| MultiConservationProblem-class | R Documentation |
Multi-objective conservation problem class
Description
This class is used to represent multi-objective conservation planning
problems. It stores the data (e.g., planning units, and features) and
mathematical formulation (e.g., the objective, constraints,
and other design criteria) needed to generate prioritizations.
Most users should use multi_problem() to generate new
multi-objective conservation problem objects, and the functions distributed
with the package to interact
with them (e.g., number_of_features(), number_of_planning_units()).
Only experts should use the fields and methods for this class directly.
Public fields
problemslistcontainingConservationProblemobjects.defaultslistindicating if other fields contain defaults.approachMultiObjApproachobject for specifying the multi-objective optimization approach.solverSolverobject specifying the solver for generating solutions.
Methods
Public methods
-
MultiConservationProblem$convert_total_unit_ids_to_indices() -
MultiConservationProblem$planning_unit_indices_with_finite_costs()
MultiConservationProblem$new()
Create a new multi-objective conservation problem object.
Usage
MultiConservationProblem$new(problems)
Arguments
problemslistcontainingConservationProblemobjects.
Returns
A new MultiConservationProblem object.
MultiConservationProblem$summary()
Print extended information about the object.
Usage
MultiConservationProblem$summary()
Returns
Invisible TRUE.
MultiConservationProblem$print()
Print concise information about the object.
Usage
MultiConservationProblem$print()
Returns
Invisible TRUE.
MultiConservationProblem$show()
Display concise information about the object.
Usage
MultiConservationProblem$show()
Returns
Invisible TRUE.
MultiConservationProblem$repr()
Generate a character representation of the object.
Usage
MultiConservationProblem$repr()
Returns
A character value.
MultiConservationProblem$number_of_planning_units()
Obtain the number of planning units. The planning units correspond to
elements in the cost data
(e.g., indices, rows, geometries, cells) that have finite
values in at least one zone. In other words, planning unit are
elements in the cost data that do not have missing (NA) values in
every zone.
Usage
MultiConservationProblem$number_of_planning_units()
Returns
An integer value.
MultiConservationProblem$is_ids_equivalent_to_indices()
Check if planning unit identifiers are equivalent to the planning
unit indices? Only FALSE if the planning units are
data.frame format.
Usage
MultiConservationProblem$is_ids_equivalent_to_indices()
Returns
A logical value.
MultiConservationProblem$planning_unit_indices()
Obtain the planning unit indices.
Usage
MultiConservationProblem$planning_unit_indices()
Returns
An integer vector.
MultiConservationProblem$total_unit_ids()
Obtain the total unit identifiers.
Usage
MultiConservationProblem$total_unit_ids()
Returns
An integer vector.
MultiConservationProblem$convert_total_unit_ids_to_indices()
Convert total unit identifiers to indices.
Usage
MultiConservationProblem$convert_total_unit_ids_to_indices(ids)
Arguments
idsintegervector with planning unit identifiers.
Returns
An integer vector.
MultiConservationProblem$planning_unit_indices_with_finite_costs()
Obtain the planning unit indices that are associated with finite cost values.
Usage
MultiConservationProblem$planning_unit_indices_with_finite_costs()
Returns
A list of integer vectors. Each list element corresponds to
a different zone.
MultiConservationProblem$number_of_total_units()
Obtain the number of total units. The total units include all elements
in the cost data
(e.g., indices, rows, geometries, cells), including those with
missing (NA) values.
Usage
MultiConservationProblem$number_of_total_units()
Returns
An integer value.
MultiConservationProblem$planning_unit_class()
Get planning unit class.
Usage
MultiConservationProblem$planning_unit_class()
Returns
A character value.
MultiConservationProblem$number_of_features()
Obtain the number of features.
Usage
MultiConservationProblem$number_of_features()
Returns
An integer value.
MultiConservationProblem$feature_names()
Obtain the names of the features.
Usage
MultiConservationProblem$feature_names()
Returns
A character vector.
MultiConservationProblem$number_of_problems()
Obtain the number of problems.
Usage
MultiConservationProblem$number_of_problems()
Returns
An integer value.
MultiConservationProblem$problem_names()
Obtain the names of the problems.
Usage
MultiConservationProblem$problem_names()
Returns
A character vector.
MultiConservationProblem$number_of_zones()
Obtain the number of zones.
Usage
MultiConservationProblem$number_of_zones()
Returns
An integer value.
MultiConservationProblem$zone_names()
Obtain the zone names.
Usage
MultiConservationProblem$zone_names()
Returns
A character vector.
MultiConservationProblem$add_approach()
Create a new object with an approach added to the problem formulation.
Usage
MultiConservationProblem$add_approach(x)
Arguments
xMultiObjApproach object.
Returns
An updated MultiConservationProblem object.
MultiConservationProblem$add_solver()
Create a new object with a solver added to the problem formulation.
Usage
MultiConservationProblem$add_solver(x)
Arguments
xSolver object.
Returns
An updated MultiConservationProblem object.
MultiConservationProblem$clone()
The objects of this class are cloneable with this method.
Usage
MultiConservationProblem$clone(deep = FALSE)
Arguments
deepWhether to make a deep clone.
See Also
Other classes:
ConservationModifier-class,
ConservationProblem-class,
Constraint-class,
Decision-class,
MultiObjApproach-class,
Objective-class,
OptimizationProblem-class,
Penalty-class,
Portfolio-class,
Solver-class,
Target-class,
TargetMethod-class,
Weight-class
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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