decogo.pyomo_problem.pyomo_master_problem

This module manages all Pyomo master problems

Classes

PyomoMasterProblems(block_model, ...)

A container class for managing all master problems

class decogo.pyomo_problem.pyomo_master_problem.PyomoMasterProblems(block_model, approx_data, strategy)

A container class for managing all master problems

Parameters

• inner_master_problem – Inner Approximation master problem

• compact_oa_master_problem – Compact OA master problem

• oa_master_problem – OA master problem with valid cuts generated after solving the sub-problems

• mip_oa_master_problem – MIP OA master with linearization cuts

• slack_mip_oa_problem (SlackMipOaMasterProblem) – MIP OA master with linearization cuts used for solving regarding fixed variables

• nlp_problem (PyomoNlpProblem) – NLP master problem

• mip_projection_master_problem – MIP projection master problem

• nlp_resource_projection_problem (NlpResourceProjectionProblem) – NLP projection master problem

__init__(block_model, approx_data, strategy)

Constructor method

solve_ia(solver_name, slack_weights=None)

Solves InnerMasterProblem

Parameters

• solver_name (str) – External solver name

• slack_weights (ndarray) – Slack weights, defaults to None

Returns

Active (selected) cells, weights for inner points, solution point in original space, solution in image space, slack values, dual solution, objective value

Return type

tuple

solve_mini_ia(solver_name, hyper_block, dir_im_space)

solve_compact_oa(solver_name, direction=None, bounds=None, solver_options=None)

Solves CompactOaMasterProblem

Parameters

• solver_name (str) – External solver name

• direction (ndarray) – Direction vector, defaults to None

• bounds (tuple) – Tuple of upper and lower resource bounds, defaults to None

• solver_options (list) – External solver options, defaults to None

Returns

Solution point, dual solution and objective value

Return type

tuple

solve_mip_proj_problem(solver_name, point_to_project, target_value=inf, pool_solutions=100)

Solves MipProjectionMasterProblem

Parameters

• solver_name (str) – External solver name

• point_to_project (BlockVector) – Point to project from, it is in the original space

Returns

Solution point, objective value

Return type

tuple

solve_agg_mip_proj_problem(solver_name, point_to_project, agg_blocks, target_value=inf, pool_solutions=10)

Solves aggregated sub-problem of MipProjectionMasterProblem. It is not full master problem anymore, instead it is an aggregated sub-problem with several blocks

Parameters

• solver_name (str) – External solver name

• point_to_project (BlockVector) – Point to project from, it is in the original space

• agg_blocks (tuple or list) – indices of atomic blocks to aggregate

• glob_con_indices (tuple or list) – indices of global constraints to consider in aggregated subproblem

Returns

Solution point, objective value

Return type

tuple

nlp_solve(solver_name, point_to_fix=None, start_point=None, cut_direction=None)

Solves NlpProblem. Solved mostly with fixed integer variables

Parameters

• solver_name (str) – External solver name

• point_to_fix (BlockVector) – Point to be fixed using the integer variables

• start_point (BlockVector) – Point for the warm start for the external solver

• cut_direction (BlockVector) – Objective direction

Returns

Solution point, objective value, flag if the solution point is feasible

Return type

tuple

agg_nlp_solve(solver_name, agg_blocks, point_to_fix=None, start_point=None, cut_direction=None)

Solves NlpProblem. Solved mostly with fixed integer variables

Parameters

• solver_name (str) – External solver name

• agg_blocks (tuple or list) – indices of atomic blocks to aggregate

• glob_con_indices (tuple or list) – indices of global constraints to consider in aggregated subproblem

• point_to_fix (BlockVector) – Point to be fixed using the integer variables

• start_point (BlockVector) – Point for the warm start for the external solver

• cut_direction (BlockVector) – Objective direction

Returns

Solution point, objective value, flag if the solution point is feasible

Return type

tuple

solve_nlp_resource_proj_problem(solver_name, point_to_project, target_value=inf, start_point=None)

Solves NlpResourceProjectionProblem

Parameters

• solver_name (str) – External solver name

• point_to_project (BlockVector) – Point to project from, it is in the image space

• start_point (BlockVector) – Starting point for external solver

Returns

Solution point, objective value, flag indicating if the solution point is infeasible, slack value of the soft fixing of target cut

Return type

tuple

solve_agg_nlp_resource_proj_problem(solver_name, point_to_project, agg_blocks, glob_con_indices, target_value=inf, start_point=None)

Solves NlpResourceProjectionProblem

Parameters

• solver_name (str) – External solver name

• point_to_project (BlockVector) – Point to project from, it is in the image space

• agg_blocks (tuple or list) – indices of atomic blocks to aggregate

• glob_con_indices (tuple or list) – indices of global constraints to consider in aggregated subproblem

• start_point (BlockVector) – Starting point for external solver

Returns

Solution point, objective value, flag indicating if the solution point is infeasible, slack value of the soft fixing of target cut

Return type

tuple

agg_minlp_solve(solver_name, agg_blocks, solver_options=None, cut_direction=None)

Solves NlpProblem as aggregated MINLP subproblem

Parameters

• solver_name (str) – External solver name

• agg_blocks (tuple or list) – indices of atomic blocks to aggregate

• glob_con_indices (tuple or list) – indices of global constraints to consider in aggregated subproblem

• cut_direction (BlockVector) – Objective direction

Returns

Solution point, objective value, flag if the solution point is feasible

Return type

tuple

solve_mip_oa(solver_name)

Solves MipOaMasterProblem

Parameters

• solver_name (str) – External solver name

• start_point (BlockVector) – Point for the warm start for the external solver

Returns

Solution point, objective value

Return type

tuple

solve_integer_relaxed_oa(solver_name)

Solves MipOaMasterProblem with relaxed integer variables

Parameters

solver_name (str) – External solver name

Returns

Solution point, objective value

Return type

tuple

solve_mipoa_with_slacks(solver_name, x, block_id)

Solves MipOaMasterProblemWithSlacks with k-th unfixed or set of unfixed blocks

Parameters

• solver_name (str) – External solver name

• x (BlockVector) – Point for fixing

• block_id (int or set) – Blocks not to fix

Returns

Solution point, objective value, flag if the slacks are zero

Return type

tuple

solve_outer_master_problem(solver_name)

Solves OaMasterProblem

Parameters

solver_name – External solver name

Returns

Solution point, objective value, dual solution

Return type

tuple

add_linearization_cuts(number_of_cuts)

Adds the last \(n\) linearization cuts

Parameters

n (dict) – Number of cuts to add

update_var_lower_bound(index)

Updates lower bound of the variable by calling update_var_lower_bound()

Parameters

index (tuple) – Index as pair (block_id, index)

update_var_upper_bound(index)

Updates lower bound of the variable by calling update_var_upper_bound()

Parameters

index (tuple) – Index as pair (block_id, index)

add_inner_point(block_id)

Adds inner point to the InnerMasterProblem by calling add_column()

Parameters

block_id (int) – Block identifier

add_lin_local_constr(block_id)

Adds linear local constraints. It takes the last local constraint stored in the model.block_model.BlockModel

Parameters

block_id (int) – Block identifier

add_compact_lin_local_constr(block_id, lhs, relation, rhs)

Adds compact linear constraint to master problems

Parameters

• block_id (int) – Block identifier

• lhs (ndarray) – Left hand side of the constraints

• relation (str) – Relation of the constraint

• rhs (float) – Right hand side of the constraint