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LSParam Class

class localsolver.LSParam

Solving parameters. This class contains some methods allowing you to parameterize the resolution of the model. For the sake of simplicity, only a few parameters are actually offered to tune the search.

Summary

Methods
set_seed Sets the seed of the pseudo-random number generator used by the solver.
get_seed Gets the seed of the pseudo-random number generator used by the solver.
set_nb_threads Sets the number of threads used to parallelize the search.
get_nb_threads Gets the number of threads.
set_annealing_level Sets the simulated annealing level.
get_annealing_level Gets the simulated annealing level.
set_verbosity Sets the verbosity level of the solver.
get_verbosity Gets the verbosity level of the solver.
set_objective_bound Sets the bound of the objective with the given index.
get_objective_bound Gets the bound of the objective with the given index.
set_time_between_displays Sets the time in seconds between two consecutive displays in console while the solver is running.
get_time_between_displays Gets the time in seconds between two consecutive displays in console while the solver is running.
set_log_file Sets the path of the LocalSolver log file.
get_log_file Returns the path of the LocalSolver log file.
set_advanced_parameter Sets the value of an advanced parameter.
get_advanced_parameter Returns the value of an advanced parameter.
Attributes
seed Seed of the pseudo-random number generator used by the solver.
nb_threads Number of threads used to parallelize the search.
annealing_level Simulated annealing level.
verbosity Verbosity level of the solver.
time_between_displays Time in seconds between two consecutive displays.
log_file Path of the LocalSolver log file.
advanced_parameters Advanced parameters.
Special methods
__str__ Returns a string representation of these parameters.

Instance methods

LSParam.set_seed(seed)

Sets the seed of the pseudo-random number generator used by the solver. The seed must be a positive integer. The default seed is set to 0. Only allowed in state LSState.STOPPED.

The search for solutions is highly randomized. Fixing the seed and the number of iterations of the solver allows you to reproduce exactly its results over several runs.

You can also use the shortcut member seed

Parameters:seed (int) – Seed of the pseudo-random number generator.
LSParam.get_seed()

Gets the seed of the pseudo-random number generator used by the solver. Only allowed in states LSState.PAUSED or LSState.STOPPED.

You can also use the shortcut member seed

Returns:Seed of the pseudo-random number generator.
Return type:int
LSParam.set_nb_threads(nb_threads)

Sets the number of threads used to parallelize the search. The number of threads must be a strictly positive integer. The default number of threads is set to 2. Only allowed in state LSState.STOPPED.

By increasing the number of threads, you increase the robustness of the solver (that is, the chance to find better solutions). However, we recommend you to avoid running a number of threads which exceeds the number of cores available on your machine. Since the performance of the solver is sensible to the number of cache misses, the recommended ratio for maximizing its efficiency is to launch at most k/2 searches with k the number of cores of your hardware.

You can also use the shortcut member nb_threads

Parameters:nb_threads (int) – Number of threads.
LSParam.get_nb_threads()

Gets the number of threads. Only allowed in states LSState.PAUSED or LSState.STOPPED.

You can also use the shortcut member nb_threads

Returns:Number of threads.
Return type:int
LSParam.set_annealing_level(level)

Sets the simulated annealing level. The level must be an integer between 0 and 9. The default simulated annealing level is set to 1. Only allowed in state LSState.STOPPED.

If set to 0, the search heuristic is equivalent to a standard descent: moves deteriorating the current solution are rejected. By increasing this parameter, you increase the number of uphill moves (that is, moves deteriorating the objective value of the current solution): this increases chances to reach better solutions (diversification), but slows the convergence of the search.

You can also use the shortcut member annealing_level

Parameters:level (int) – Simulated annealing level.
LSParam.get_annealing_level()

Gets the simulated annealing level. Only allowed in states LSState.PAUSED or LSState.STOPPED.

You can also use the shortcut member annealing_level

Returns:Simulated annealing level.
Return type:int
LSParam.set_verbosity(verbosity)

Sets the verbosity level of the solver. The default verbosity is set to 1. There are 3 defined verbosity levels :

  • 0 : All the traces are disabled.
  • 1 : Normal verbosity. This is the default level.
  • 2 : Detailed verbosity. Displays statistics during the search.

You can also use the shortcut member verbosity

Parameters:verbosity (int) – Verbosity level: 0, 1, 2.
LSParam.get_verbosity()

Gets the verbosity level of the solver.

You can also use the shortcut member verbosity

Returns:verbosity Verbosity level: 0, 1 or 2.
Return type:int
LSParam.set_objective_bound(obj_index, bound)

Sets the bound of the objective with the given index. If the objective is minimized (respectively maximized), then the optimization of this objective is stopped as soon as this lower (respectively upper) bound is reached. It can be useful for goal programming. Only allowed in states LSState.STOPPED.

Parameters:
  • obj_index (int) – Index of the objective
  • bound – Objective bound. The bound can be a double or an integer.
LSParam.get_objective_bound(obj_index)

Gets the bound of the objective with the given index. Only allowed in states LSState.PAUSED or LSState.STOPPED.

Parameters:obj_index (int) – Index of the objective
Returns:The bound of the objective
Return type:int or double
LSParam.set_time_between_displays(time_between_displays)

Sets the time in seconds between two consecutive displays in console while the solver is running. The default time between displays is set to 1 second. Only allowed in state LSState.STOPPED.

You can also use the shortcut member time_between_displays

Parameters:time_between_displays (int) – Time in seconds between displays.
LSParam.get_time_between_displays()

Gets the time in seconds between two consecutive displays in console while the solver is running. Only allowed in states LSState.PAUSED or LSState.STOPPED.

You can also use the shortcut member time_between_displays

Returns:Time in seconds between displays.
Return type:int
LSParam.set_log_file(path)

Sets the path of the LocalSolver log file. If the path is empty, no log will be saved. To tune the logging verbosity, see set_verbosity(). Only allowed in states LSState.STOPPED or LSState.MODELING.

You can also use the shortcut member log_file

Parameters:path (str) – Path of the log file. Leave empty to disable the file logging mechanism.
LSParam.get_log_file()

Returns the path of the LocalSolver log file. If no log file was specified, an empty string is returned.

You can also use the shortcut member log_file

Returns:The path of the log file or an empty string.
Return type:str
LSParam.set_advanced_parameter(key, value)

Sets the value of an advanced parameter. Advanced parameters are reserved for fine tuning or debugging and should not be used by end-users. Only allowed in states LSState.STOPPED or LSState.MODELING.

Advanced parameters can have string or integer values. You can also use the shortcut collection member advanced_parameters.

Parameters:
  • key (str) – Name of the parameter to change
  • value – Value of the parameter. The value can be an integer or a string.
LSParam.get_advanced_parameter(key, value)

Returns the value of an advanced parameter. Advanced parameters are reserved for fine tuning or debugging and should not be used by end-users. Throws an exception if the parameter does not exist. Only allowed in states LSState.PAUSED or LSState.STOPPED.

Advanced parameters can have string or integer values. You can also use the shortcut collection member advanced_parameters.

Parameters:key (str) – Name of the parameter
Returns:Value of the parameter
Return type:Integer or string

Instance attributes

All get/set methods have their attribute counterpart. You can use them as shortcuts to improve the readability or your models and codes.

LSParam.seed

Seed of the pseudo-random number generator used by the solver. It is a shortcut for get_seed() and set_seed().

LSParam.nb_threads

Number of threads used to parallelize the search. It is a shortcut for get_nb_threads() and set_nb_threads().

LSParam.annealing_level

Simulated annealing level. It is a shortcut for get_annealing_level() and set_annealing_level().

LSParam.verbosity

Verbosity level of the solver. It is a shortcut for get_verbosity() and set_verbosity().

LSParam.time_between_displays

Time in seconds between two consecutive displays. It is a shortcut for get_time_between_displays() and set_time_between_displays().

LSParam.log_file

Path of the LocalSolver log file. It is a shortcut for get_log_file() and set_log_file().

LSParam.advanced_parameters

Advanced parameters. It is a shortcut for get_advanced_parameter() and set_advanced_parameter(). The returned object can be indexed with strings. Please not that it is not iterable and you cannot apply the function len on it.

Special operators and methods

LSParam.__str__()

Returns a string representation of these parameters. Useful for debugging or logging purposes.

Returns:String representation.
Return type:str