DenseLP Class |
Namespace: Imsl.Math
The DenseLP type exposes the following members.
Name | Description | |
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DenseLP(MPSReader) |
Constructor using an MPSReader object.
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DenseLP(Double, Double, Double) |
Constructor variables of type double.
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Name | Description | |
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Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | |
Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) | |
GetDualSolution |
Returns the dual solution.
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GetHashCode | Serves as a hash function for a particular type. (Inherited from Object.) | |
GetSolution |
Returns the solution x of the linear programming problem.
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GetType | Gets the Type of the current instance. (Inherited from Object.) | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |
SetConstraintType |
Sets the types of general constraints in the matrix a.
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SetLowerBound |
Sets the lower bound, on the variables.
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SetUpperBound |
Sets the upper bound, on the variables.
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SetUpperLimit |
Sets the upper limit of the constraints.
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Solve |
Solves the problem using an active set strategy.
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ToString | Returns a string that represents the current object. (Inherited from Object.) |
Name | Description | |
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IterationCount |
Returns the number of iterations used.
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ObjectiveValue |
Returns the optimal value of the objective function.
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RefinementType |
The type of refinement used, if any.
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Class DenseLP uses an active set strategy to solve linear programming problems, i.e., problems of the form
subject to
where c is the objective coefficient vector, A is the coefficient matrix, and the vectors , , , and are the lower and upper bounds on the constraints and the variables, respectively.
If the linear constraints are infeasible an solution to the constraints are used as a replacement for the stated constraints. An exception is thrown but a generalized solution is computed and available using methods GetSolution or GetDualSolution. Similar comments hold for any of the three additional conditions:
Refer to the following paper for further information: Krogh, Fred, T. (2005), An Algorithm for Linear Programming, http://mathalacarte.com/fkrogh/pub/lp.pdf , Tujunga, CA.