Protobuf enum operations_research.pdlp.PrimalDualHybridGradientParams.RestartStrategy
Definition at line 77 of file PrimalDualHybridGradientParams.java.
◆ [static initializer]()
| com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.[static initializer] |
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◆ forNumber()
| static RestartStrategy com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.forNumber |
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- Parameters
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| value | The numeric wire value of the corresponding enum entry. |
- Returns
- The enum associated with the given numeric wire value.
Definition at line 204 of file PrimalDualHybridGradientParams.java.
◆ getDescriptor()
| static final com.google.protobuf.Descriptors.EnumDescriptor com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.getDescriptor |
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◆ getDescriptorForType()
| final com.google.protobuf.Descriptors.EnumDescriptor com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.getDescriptorForType |
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◆ getNumber()
| final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.getNumber |
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◆ getValueDescriptor()
| final com.google.protobuf.Descriptors.EnumValueDescriptor com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.getValueDescriptor |
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◆ internalGetValueMap()
| static com.google.protobuf.Internal.EnumLiteMap< RestartStrategy > com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.internalGetValueMap |
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◆ valueOf() [1/2]
| static RestartStrategy com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.valueOf |
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com.google.protobuf.Descriptors.EnumValueDescriptor | desc | ) |
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◆ valueOf() [2/2]
| static RestartStrategy com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.valueOf |
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int | value | ) |
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◆ ADAPTIVE_DISTANCE_BASED
| com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.ADAPTIVE_DISTANCE_BASED =(4) |
A distance-based restarting scheme that restarts the algorithm whenever
an appropriate potential function is reduced sufficiently. This check
happens at every major iteration.
TODO(user): Cite paper for the restart strategy and definition of the
potential function, when available.
ADAPTIVE_DISTANCE_BASED = 4;
Definition at line 125 of file PrimalDualHybridGradientParams.java.
◆ ADAPTIVE_DISTANCE_BASED_VALUE
| final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.ADAPTIVE_DISTANCE_BASED_VALUE = 4 |
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A distance-based restarting scheme that restarts the algorithm whenever
an appropriate potential function is reduced sufficiently. This check
happens at every major iteration.
TODO(user): Cite paper for the restart strategy and definition of the
potential function, when available.
ADAPTIVE_DISTANCE_BASED = 4;
Definition at line 183 of file PrimalDualHybridGradientParams.java.
◆ ADAPTIVE_HEURISTIC
| com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.ADAPTIVE_HEURISTIC =(3) |
A heuristic that adaptively decides on every major iteration whether to
restart (this is forced approximately on increasing powers-of-two
iterations), and if so to the current or to the average, based on
reduction in a potential function. The rule more or less follows the
description of the adaptive restart scheme in
https://arxiv.org/pdf/2106.04756.pdf.
ADAPTIVE_HEURISTIC = 3;
Definition at line 113 of file PrimalDualHybridGradientParams.java.
◆ ADAPTIVE_HEURISTIC_VALUE
| final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.ADAPTIVE_HEURISTIC_VALUE = 3 |
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A heuristic that adaptively decides on every major iteration whether to
restart (this is forced approximately on increasing powers-of-two
iterations), and if so to the current or to the average, based on
reduction in a potential function. The rule more or less follows the
description of the adaptive restart scheme in
https://arxiv.org/pdf/2106.04756.pdf.
ADAPTIVE_HEURISTIC = 3;
Definition at line 171 of file PrimalDualHybridGradientParams.java.
◆ EVERY_MAJOR_ITERATION
| com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.EVERY_MAJOR_ITERATION =(2) |
On every major iteration, the current solution is reset to the average
since the last major iteration.
EVERY_MAJOR_ITERATION = 2;
Definition at line 100 of file PrimalDualHybridGradientParams.java.
◆ EVERY_MAJOR_ITERATION_VALUE
| final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.EVERY_MAJOR_ITERATION_VALUE = 2 |
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On every major iteration, the current solution is reset to the average
since the last major iteration.
EVERY_MAJOR_ITERATION = 2;
Definition at line 158 of file PrimalDualHybridGradientParams.java.
◆ NO_RESTARTS
| com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.NO_RESTARTS =(1) |
No restarts are performed. The average solution is cleared every major
iteration, but the current solution is not changed.
NO_RESTARTS = 1;
Definition at line 91 of file PrimalDualHybridGradientParams.java.
◆ NO_RESTARTS_VALUE
| final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.NO_RESTARTS_VALUE = 1 |
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No restarts are performed. The average solution is cleared every major
iteration, but the current solution is not changed.
NO_RESTARTS = 1;
Definition at line 149 of file PrimalDualHybridGradientParams.java.
◆ RESTART_STRATEGY_UNSPECIFIED
| com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.RESTART_STRATEGY_UNSPECIFIED =(0) |
◆ RESTART_STRATEGY_UNSPECIFIED_VALUE
| final int com.google.ortools.pdlp.PrimalDualHybridGradientParams.RestartStrategy.RESTART_STRATEGY_UNSPECIFIED_VALUE = 0 |
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The documentation for this enum was generated from the following file:
1.13.2