Parameters with prefix separating/rapidlearning. More...
Variables | |
constexpr Param< bool > | APPLYBDCHGS { "separating/rapidlearning/applybdchgs" } |
should the found global bound deductions be applied in the original SCIP? | |
constexpr Param< bool > | APPLYCONFLICTS { "separating/rapidlearning/applyconflicts" } |
should the found conflicts be applied in the original SCIP? | |
constexpr Param< bool > | APPLYINFERVALS { "separating/rapidlearning/applyinfervals" } |
should the inference values be used as initialization in the original SCIP? | |
constexpr Param< bool > | APPLYPRIMALSOL { "separating/rapidlearning/applyprimalsol" } |
should the incumbent solution be copied to the original SCIP? | |
constexpr Param< bool > | APPLYSOLVED { "separating/rapidlearning/applysolved" } |
should a solved status be copied to the original SCIP? | |
constexpr Param< bool > | CHECKDEGENERACY { "separating/rapidlearning/checkdegeneracy" } |
should local LP degeneracy be checked? | |
constexpr Param< bool > | CHECKDUALBOUND { "separating/rapidlearning/checkdualbound" } |
should the progress on the dual bound be checked? | |
constexpr Param< bool > | CHECKEXEC { "separating/rapidlearning/checkexec" } |
check whether rapid learning should be executed | |
constexpr Param< bool > | CHECKLEAVES { "separating/rapidlearning/checkleaves" } |
should the ratio of leaves proven to be infeasible and exceeding the cutoff bound be checked? | |
constexpr Param< bool > | CHECKNSOLS { "separating/rapidlearning/checknsols" } |
should the number of solutions found so far be checked? | |
constexpr Param< bool > | CHECKOBJ { "separating/rapidlearning/checkobj" } |
should the (local) objective function be checked? | |
constexpr Param< bool > | CONTVARS { "separating/rapidlearning/contvars" } |
should rapid learning be applied when there are continuous variables? | |
constexpr Param< double > | CONTVARSQUOT { "separating/rapidlearning/contvarsquot" } |
maximal portion of continuous variables to apply rapid learning | |
constexpr Param< bool > | COPYCUTS { "separating/rapidlearning/copycuts" } |
should all active cuts from cutpool be copied to constraints in subproblem? | |
constexpr Param< bool > | DELAY { "separating/rapidlearning/delay" } |
should separator be delayed, if other separators found cuts? | |
constexpr Param< int > | EXPBACKOFF { "separating/rapidlearning/expbackoff" } |
base for exponential increase of frequency at which separator <rapidlearning> is called (1: call at each multiple of frequency) | |
constexpr Param< int > | FREQ { "separating/rapidlearning/freq" } |
frequency for calling separator <rapidlearning> (-1: never, 0: only in root node) | |
constexpr Param< double > | LPITERQUOT { "separating/rapidlearning/lpiterquot" } |
maximal fraction of LP iterations compared to node LP iterations | |
constexpr Param< double > | MAXBOUNDDIST { "separating/rapidlearning/maxbounddist" } |
maximal relative distance from current node's dual bound to primal bound compared to best node's dual bound for applying separator <rapidlearning> (0.0: only on current best node, 1.0: on all nodes) | |
constexpr Param< int > | MAXCALLS { "separating/rapidlearning/maxcalls" } |
maximum number of overall calls | |
constexpr Param< int > | MAXNCONSS { "separating/rapidlearning/maxnconss" } |
maximum problem size (constraints) for which rapid learning will be called | |
constexpr Param< int > | MAXNODES { "separating/rapidlearning/maxnodes" } |
maximum number of nodes considered in rapid learning run | |
constexpr Param< int > | MAXNVARS { "separating/rapidlearning/maxnvars" } |
maximum problem size (variables) for which rapid learning will be called | |
constexpr Param< double > | MINDEGENERACY { "separating/rapidlearning/mindegeneracy" } |
minimal degeneracy threshold to allow local rapid learning | |
constexpr Param< double > | MININFLPRATIO { "separating/rapidlearning/mininflpratio" } |
minimal threshold of inf/obj leaves to allow local rapid learning | |
constexpr Param< int > | MINNODES { "separating/rapidlearning/minnodes" } |
minimum number of nodes considered in rapid learning run | |
constexpr Param< double > | MINVARCONSRATIO { "separating/rapidlearning/minvarconsratio" } |
minimal ratio of unfixed variables in relation to basis size to allow local rapid learning | |
constexpr Param< long long > | NWAITINGNODES { "separating/rapidlearning/nwaitingnodes" } |
number of nodes that should be processed before rapid learning is executed locally based on the progress of the dualbound | |
constexpr Param< int > | PRIORITY { "separating/rapidlearning/priority" } |
priority of separator <rapidlearning> | |
constexpr Param< bool > | REDUCEDINFER { "separating/rapidlearning/reducedinfer" } |
should the inference values only be used when rapidlearning found other reductions? | |
Parameters with prefix separating/rapidlearning.
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constexpr |
should the found global bound deductions be applied in the original SCIP?
Definition at line 6811 of file parameters.hpp.
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constexpr |
should the found conflicts be applied in the original SCIP?
Definition at line 6809 of file parameters.hpp.
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constexpr |
should the inference values be used as initialization in the original SCIP?
Definition at line 6813 of file parameters.hpp.
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constexpr |
should the incumbent solution be copied to the original SCIP?
Definition at line 6817 of file parameters.hpp.
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constexpr |
should a solved status be copied to the original SCIP?
Definition at line 6819 of file parameters.hpp.
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constexpr |
should local LP degeneracy be checked?
Definition at line 6821 of file parameters.hpp.
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constexpr |
should the progress on the dual bound be checked?
Definition at line 6823 of file parameters.hpp.
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constexpr |
check whether rapid learning should be executed
Definition at line 6827 of file parameters.hpp.
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constexpr |
should the ratio of leaves proven to be infeasible and exceeding the cutoff bound be checked?
Definition at line 6825 of file parameters.hpp.
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constexpr |
should the number of solutions found so far be checked?
Definition at line 6831 of file parameters.hpp.
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constexpr |
should the (local) objective function be checked?
Definition at line 6829 of file parameters.hpp.
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constexpr |
should rapid learning be applied when there are continuous variables?
Definition at line 6833 of file parameters.hpp.
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constexpr |
maximal portion of continuous variables to apply rapid learning
Definition at line 6835 of file parameters.hpp.
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constexpr |
should all active cuts from cutpool be copied to constraints in subproblem?
Definition at line 6858 of file parameters.hpp.
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constexpr |
should separator be delayed, if other separators found cuts?
Definition at line 6804 of file parameters.hpp.
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constexpr |
base for exponential increase of frequency at which separator <rapidlearning> is called (1: call at each multiple of frequency)
Definition at line 6807 of file parameters.hpp.
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constexpr |
frequency for calling separator <rapidlearning> (-1: never, 0: only in root node)
Definition at line 6799 of file parameters.hpp.
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constexpr |
maximal fraction of LP iterations compared to node LP iterations
Definition at line 6837 of file parameters.hpp.
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constexpr |
maximal relative distance from current node's dual bound to primal bound compared to best node's dual bound for applying separator <rapidlearning> (0.0: only on current best node, 1.0: on all nodes)
Definition at line 6802 of file parameters.hpp.
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maximum number of overall calls
Definition at line 6849 of file parameters.hpp.
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maximum problem size (constraints) for which rapid learning will be called
Definition at line 6847 of file parameters.hpp.
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maximum number of nodes considered in rapid learning run
Definition at line 6851 of file parameters.hpp.
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maximum problem size (variables) for which rapid learning will be called
Definition at line 6845 of file parameters.hpp.
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minimal degeneracy threshold to allow local rapid learning
Definition at line 6839 of file parameters.hpp.
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minimal threshold of inf/obj leaves to allow local rapid learning
Definition at line 6841 of file parameters.hpp.
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minimum number of nodes considered in rapid learning run
Definition at line 6853 of file parameters.hpp.
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minimal ratio of unfixed variables in relation to basis size to allow local rapid learning
Definition at line 6843 of file parameters.hpp.
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number of nodes that should be processed before rapid learning is executed locally based on the progress of the dualbound
Definition at line 6856 of file parameters.hpp.
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priority of separator <rapidlearning>
Definition at line 6797 of file parameters.hpp.
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should the inference values only be used when rapidlearning found other reductions?
Definition at line 6815 of file parameters.hpp.