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IloCP
.
An enumeration for the class IloCP
.
Integer parameters.
Fields |
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DefaultInferenceLevel = 1 | This parameter specifies the general inference level for constraints
whose particular inference level is |
AllDiffInferenceLevel = 2 | This parameter specifies the inference level for every constraint
Possible values for this parameter are
|
DistributeInferenceLevel = 3 | This parameter specifies the inference level for every constraint
|
CountInferenceLevel = 4 | This parameter specifies the inference level for every constraint
|
SequenceInferenceLevel = 5 | This parameter specifies the inference level for every constraint
|
AllMinDistanceInferenceLevel = 6 | This parameter specifies the inference level for every constraint
|
ElementInferenceLevel = 7 | This parameter specifies the inference level for every element
constraint (created from |
FailLimit = 9 | This parameter limits the number of failures that can occur before
terminating the search. The possible values of this parameter range
from 0 to |
ChoicePointLimit = 10 | This parameter limits the number of choice points that are created
before terminating a search. The possible values of this parameter
range from 0 to |
LogVerbosity = 11 | This parameter determines the verbosity of the search log.
The possible values are Note
The CP Optimizer search log is meant for visual inspection
only, not for mechanized parsing. In particular, the log may change
from version to version of CP Optimizer in order to improve the
quality of information displayed in the log. Any code based on the
log output for correct functioning may have to be updated when
a new version of CP Optimizer is released.
|
LogPeriod = 12 | The CP Optimizer search log includes information that is displayed
periodically. This parameter controls how often that information
is displayed. By setting this parameter to a value of
|
SearchType = 13 | Integer control parameter. This parameter determines the type of search that is applied when solving a problem.
When set to |
RandomSeed = 14 | The search uses some randomization in some strategies. This parameter
sets the seed of the random generator used by these strategies
Possible values range from 0 to |
RestartFailLimit = 15 | When |
MultiPointNumberOfSearchPoints = 16 | This parameter controls the number of (possibly partial) solutions manipulated by the multi-point search algorithm. The default value is 30. A larger value will diversify the search, with possible improvement in solution quality at the expense of a longer run time. A smaller value will intensify the search, resulting in faster convergence at the expense of solution quality. Note that memory consumption increases proportionally to this parameter, for each search point must store each decision variable domain. |
Workers = 25 | This parameter sets the number of workers to run in parallel to solve your model. If the number of workers is set to n (with n greater than one), the CP optimizer will create n workers, each in their own thread, that will work together to solve the problem. The emphasis of these workers is more to find better feasible solutions and then to speed up the proof of optimality. The default value is Note that the memory required by CP Optimizer grows roughly linearly as the number of workers is increased. If you are solving a very large model on a multi-core processor and memory usage is an issue, it is advisable to specify a reduced number of workers, or even one worker, rather than use the default value. |
BranchLimit = 28 | This parameter limits the number of branches that are made
before terminating a search. A branch is a decision
made at a choice point in the search, a typical node being made up of
two branches, for example: |
AutomaticReplay = 29 | Deprecated:
Since V12.8.0.
This parameter has no effect and is present for compatibility reasons. Its use has been deprecated since V12.8.0. |
DynamicProbing = 32 |
This parameter controls probing carried out during search.
Probing can be useful on some problems as it can make stronger
inferences on combinations of constraints.
Possible values for this parameter are |
SolutionLimit = 35 | This parameter limits the number of feasible solutions that are found
before terminating a search.
The possible values of this parameter
range from 0 to |
PrecedenceInferenceLevel = 38 | This parameter specifies the inference level for precedence
constraints between interval variables extracted to the
invoking Possible values
for this parameter are |
IntervalSequenceInferenceLevel = 39 | This parameter specifies the inference level for the
maintenance of the domain of every interval sequence variable
Possible values for this
parameter are For more information on interval sequence variables see the concept Interval variable sequencing in CP Optimizer. |
NoOverlapInferenceLevel = 40 | This parameter specifies the inference level for every
constraint For more information on no-overlap constraints see the concept Interval variable sequencing in CP Optimizer. |
CumulFunctionInferenceLevel = 41 | This parameter specifies the inference level for constraints
on expressions For more information on cumul function expressions, see the concept Cumul functions in CP Optimizer. |
StateFunctionInferenceLevel = 42 | This parameter specifies the inference level for constraints
on state functions For more information on state functions, see the concept State functions in CP Optimizer. |
TimeMode = 43 |
This parameter defines how time is measured in CP Optimizer,
the two legal values being |
TemporalRelaxation = 44 | This advanced parameter can be used to control the usage of
a temporal relaxation internal to the invoking
|
Presolve = 60 | This parameter controls the presolve of the model to
produce more compact formulations and to achieve more domain reduction.
Possible values for this parameter are |
ConflictRefinerIterationLimit = 61 | This parameter limits the number of iterations that are made before
terminating the conflict refiner. The possible values of this parameter range
from 0 to |
ConflictRefinerBranchLimit = 62 | This parameter limits the total number of branches that are made before
terminating the conflict refiner. The possible values of this parameter range
from 0 to |
ConflictRefinerFailLimit = 63 | This parameter limits the total number of failures that can occur before
terminating the conflict refiner. The possible values of this parameter range
from 0 to |
ConflictRefinerOnVariables = 64 | This parameter specifies whether the conflict refiner should refine variables
domains. Possible values for this parameter are |
ModelAnonymizer = 77 | This parameter controls anonymization of a model
dumped via |
FailureDirectedSearch = 78 | This parameter controls usage of failure-directed search. Failure-directed search assumes that there is no (better) solution or that such a solution is very hard to find. Therefore it focuses on a systematic exploration of the search space, first eliminating assignments that are most likely to fail. Failure-directed search is used only for scheduling problems (i.e.
models containing interval variables) and only when the parameter
SearchType is set to
Legal values for the |
FailureDirectedSearchMaxMemory = 79 | This parameter controls the maximum amount of memory (in bytes) available to failure-directed search (see FailureDirectedSearchMaxMemory). The default value is 104,857,600 (100MB). Failure-directed search can sometimes consume a lot of memory, especially when end times of interval variables are not bounded. Therefore it is usually not started immediately, but only when the effective horizon (time period over which CP Optimizer must reason) becomes small enough for failure-directed search to operate inside the memory limit specified by this parameter. For many types of scheduling problems, the effective horizon tends to reduce when CP Optimizer finds a better solution (often most significantly when the initial solution is found). Therefore, when each new solution is found, CP Optimizer decides whether or not to turn on failure-directed search. Note that this parameter does not influence the effectiveness of failure-directed search, once started. Its purpose is only to control the point at which failure-directed search will begin to function. |
WarningLevel = 90 | This parameter controls the level of warnings issued by CP Optimizer when a solve is launched. Specifically, all warnings of level higher than this parameter are masked. Since CP Optimizer warning levels run from 1 to 3, setting this parameter to 0 turns off all warnings. Warnings issued may indicate potential errors or inefficiencies in your model. The default value of this parameter is 2. See also PrintModelDetailsInMessages. |
UseFileLocations = 100 | This parameter controls whether CP Optimizer processes file locations.
With each constraint, variable or expression it is possible to
associate a source file location (file name and line
number). CP Optimizer can use locations later for reporting
errors and conflicts. Locations are also included in exported/dumped
models ( Source file locations can be provided to CP Optimizer in the following ways:
Legal values for this parameter are |
CountDifferentInferenceLevel = 104 | This parameter specifies the inference level for every constraint
Possible values for this parameter are
|
LogSearchTags = 107 | This parameter controls the log activation. When set to |
PrintModelDetailsInMessages = 109 | Whenever CP Optimizer prints an error or warning message, it can also
print the relevant part of the input model (in the CPO file format).
This parameter controls printing of this additional information.
Possible values are See also WarningLevel. |
KPIDisplay = 145 | This parameter determines how KPIs are displayed during the search.
The default value is |