Optimization problem class

This class is used to represent an optimization problem. It stores the information needed to generate a solution using an exact algorithm solver. Most users should use compile() to generate new optimization problem objects, and the functions distributed with the package to interact with them (e.g., base::as.list()). Only experts should use the fields and methods for this class directly.

See also

Other classes: ConservationModifier-class, ConservationProblem-class, Constraint-class, Decision-class, Objective-class, Penalty-class, Portfolio-class, Solver-class, Target-class

Public fields

ptr

A Rcpp::Xptr external pointer. Create a new optimization problem object.

Methods

Public methods

• OptimizationProblem$new()

• OptimizationProblem$print()

• OptimizationProblem$show()

• OptimizationProblem$ncol()

• OptimizationProblem$nrow()

• OptimizationProblem$ncell()

• OptimizationProblem$modelsense()

• OptimizationProblem$vtype()

• OptimizationProblem$obj()

• OptimizationProblem$A()

• OptimizationProblem$rhs()

• OptimizationProblem$sense()

• OptimizationProblem$lb()

• OptimizationProblem$ub()

• OptimizationProblem$number_of_features()

• OptimizationProblem$number_of_planning_units()

• OptimizationProblem$number_of_zones()

• OptimizationProblem$col_ids()

• OptimizationProblem$row_ids()

• OptimizationProblem$compressed_formulation()

• OptimizationProblem$shuffle_columns()

• OptimizationProblem$clone()

---

Method new()

Usage

OptimizationProblem$new(ptr)

Arguments

ptr

Rcpp::Xptr external pointer.

Returns

A new OptimizationProblem object.

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Method print()

Print concise information about the object.

Usage

OptimizationProblem$print()

Returns

Invisible TRUE.

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Method show()

Print concise information about the object.

Usage

OptimizationProblem$show()

Returns

Invisible TRUE.

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Method ncol()

Obtain the number of columns in the problem formulation.

Usage

OptimizationProblem$ncol()

Returns

A numeric value.

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Method nrow()

Obtain the number of rows in the problem formulation.

Usage

OptimizationProblem$nrow()

Returns

A numeric value.

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Method ncell()

Obtain the number of cells in the problem formulation.

Usage

OptimizationProblem$ncell()

Returns

A numeric value.

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Method modelsense()

Obtain the model sense.

Usage

OptimizationProblem$modelsense()

Returns

A character value.

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Method vtype()

Obtain the decision variable types.

Usage

OptimizationProblem$vtype()

Returns

A character vector.

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Method obj()

Obtain the objective function.

Usage

OptimizationProblem$obj()

Returns

A numeric vector.

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Method A()

Obtain the constraint matrix.

Usage

OptimizationProblem$A()

Returns

A Matrix::sparseMatrix() object.

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Method rhs()

Obtain the right-hand-side constraint values.

Usage

OptimizationProblem$rhs()

Returns

A numeric vector.

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Method sense()

Obtain the constraint senses.

Usage

OptimizationProblem$sense()

Returns

A character vector.

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Method lb()

Obtain the lower bounds for the decision variables.

Usage

OptimizationProblem$lb()

Returns

A numeric vector.

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Method ub()

Obtain the upper bounds for the decision variables.

Usage

OptimizationProblem$ub()

Returns

A numeric vector.

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Method number_of_features()

Obtain the number of features.

Usage

OptimizationProblem$number_of_features()

Returns

A numeric value.

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Method number_of_planning_units()

Obtain the number of planning units.

Usage

OptimizationProblem$number_of_planning_units()

Returns

A numeric value.

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Method number_of_zones()

Obtain the number of zones.

Usage

OptimizationProblem$number_of_zones()

Returns

A numeric value.

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Method col_ids()

Obtain the identifiers for the columns.

Usage

OptimizationProblem$col_ids()

Returns

A character value.

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Method row_ids()

Obtain the identifiers for the rows.

Usage

OptimizationProblem$row_ids()

Returns

A character value.

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Method compressed_formulation()

Is the problem formulation compressed?

Usage

OptimizationProblem$compressed_formulation()

Returns

A logical value.

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Method shuffle_columns()

Shuffle the order of the columns in the conservation problem.

Usage

OptimizationProblem$shuffle_columns()

Returns

integer vector with indices to un-shuffle the problem.

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Method clone()

The objects of this class are cloneable with this method.

Usage

OptimizationProblem$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.