Package org.ojalgo.optimisation.convex
Class ConvexSolver.Builder
java.lang.Object
org.ojalgo.optimisation.GenericSolver.Builder<ConvexSolver.Builder,ConvexSolver>
org.ojalgo.optimisation.convex.ConvexSolver.Builder
- All Implemented Interfaces:
Optimisation
,Optimisation.ProblemStructure
- Enclosing class:
ConvexSolver
public static final class ConvexSolver.Builder
extends GenericSolver.Builder<ConvexSolver.Builder,ConvexSolver>
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Nested Class Summary
Nested classes/interfaces inherited from interface org.ojalgo.optimisation.Optimisation
Optimisation.Constraint, Optimisation.ConstraintType, Optimisation.Integration<M extends Optimisation.Model,
S extends Optimisation.Solver>, Optimisation.Model, Optimisation.Objective, Optimisation.Options, Optimisation.ProblemStructure, Optimisation.Result, Optimisation.Sense, Optimisation.Solver, Optimisation.State -
Field Summary
Fields inherited from interface org.ojalgo.optimisation.Optimisation.ProblemStructure
DEBUG
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionprotected void
append
(StringBuilder builder) protected ConvexSolver
doBuild
(Optimisation.Options options) equalities
(Access2D<?> mtrxAE, Access1D<?> mtrxBE) equality
(double rhs, double... factors) protected PhysicalStore
<Double> getC()
Linear objective: [C]protected <N extends Comparable<N>>
ConvexData<N> getConvexData
(PhysicalStore.Factory<N, ?> factory) protected PhysicalStore
<Double> getQ()
Quadratic objective: [Q]inequalities
(Access2D<?> mtrxAI, Access1D<?> mtrxBI) inequality
(double rhs, double... factors) linear
(double... factors) Set the linear part of the objective functionSet the linear part of the objective functionobjective
(int index, double value) Set one element of the linear part of the objective functionobjective
(int row, int col, double value) Set one element of the quadratic part of the objective functionobjective
(MatrixStore<?> mtrxQ, MatrixStore<?> mtrxC) Set the quadratic part of the objective functionDisregard the objective function (set it to zero) and form the dual LP.Approximate at origin (0.0 vector)toLinearApproximation
(Access1D<Double> point) Linearise the objective function (at the specified point) and duplicate all variables to handle the (potential) positive and negative parts separately.Methods inherited from class org.ojalgo.optimisation.GenericSolver.Builder
append, build, build, countAdditionalConstraints, countEqualityConstraints, countInequalityConstraints, countVariables, doCountVariables, getAE, getAE, getAE, getAI, getAI, getAI, getBE, getBE, getBI, getBI, getFactory, getLowerBounds, getObjective, getRowsAE, getRowsAI, getUpperBounds, reset, setNumberOfVariables, setObjective, solve, toString
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface org.ojalgo.optimisation.Optimisation.ProblemStructure
countConstraints
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Constructor Details
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Builder
Builder() -
Builder
Builder(int nbVariables) -
Builder
Builder(MatrixStore<Double>[] matrices)
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Method Details
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equalities
- Overrides:
equalities
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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equality
- Overrides:
equality
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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getObjective
- Overrides:
getObjective
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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inequalities
- Overrides:
inequalities
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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inequality
- Overrides:
inequality
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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linear
Set the linear part of the objective function -
linear
Set the linear part of the objective function -
objective
Set one element of the linear part of the objective function -
objective
Set one element of the quadratic part of the objective function -
objective
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quadratic
Set the quadratic part of the objective function -
toFeasibilityChecker
Disregard the objective function (set it to zero) and form the dual LP. -
toLinearApproximation
Approximate at origin (0.0 vector)- See Also:
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toLinearApproximation
Linearise the objective function (at the specified point) and duplicate all variables to handle the (potential) positive and negative parts separately. -
append
- Overrides:
append
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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doBuild
- Specified by:
doBuild
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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getC
Linear objective: [C]- Overrides:
getC
in classGenericSolver.Builder<ConvexSolver.Builder,
ConvexSolver>
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getConvexData
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getQ
Quadratic objective: [Q]
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