jijzept_solver.solver_components

Module Contents

alm_simulated_annealing_solver(converted_ommx_instance_buf, id_translator, initial_ommx_state_buf, num_samples, seed, option, log_display=False, log_interval_sec=None, global_start_time=None)
Parameters:
Return type:

list[list[tuple[int, float]]]

cbc_solver(converted_ommx_instance, option, initial_ommx_state=None)

Solve an optimization problem using the CBC solver via the OMMXPythonMIPAdapter.

Parameters:
  • converted_ommx_instance (Instance) – The OMMX problem instance to solve.

  • option (CBCOption) – Solver options, including time limits.

  • initial_ommx_state (Optional[State], optional) – An initial solution state. Not used by this solver, but included for interface compatibility.

Returns:

The solution found by the CBC solver.

Return type:

Solution

Raises:

Exception – If the underlying solver fails or encounters an error during optimization.

convert_to_samples(result, converted_ommx_instance)
Parameters:
Return type:

ommx.v1.Samples

local_ilp_solver(converted_ommx_instance_buf, id_translator, initial_ommx_state_buf, num_samples, seed, option, log_display=False, log_interval_sec=None, global_start_time=None)
Parameters:
Return type:

list[list[tuple[int, float]]]

scip_solver(converted_ommx_instance, option, initial_ommx_state=None)
Parameters:
Return type:

ommx.v1.Solution

weighted_hill_climbing_solver(converted_ommx_instance_buf, id_translator, initial_ommx_state_buf, num_samples, seed, option, log_display=False, log_interval_sec=None, global_start_time=None)
Parameters:
Return type:

list[list[tuple[int, float]]]

weighted_simulated_annealing_solver(converted_ommx_instance_buf, id_translator, initial_ommx_state_buf, num_samples, seed, option, log_display=False, log_interval_sec=None, global_start_time=None)
Parameters:
Return type:

list[list[tuple[int, float]]]