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/dports/math/alberta/alberta3-920315ae1bbfd1b1fb6672d916619ac37a411e95/add_ons/albertasystems/AlbertaNum/Common/
H A Dsolve_multiphase.h1 struct solve_data struct
9 typedef struct solve_data SOLVE_DATA; argument
/dports/math/py-Pyomo/Pyomo-6.1.2/pyomo/contrib/mindtpy/
H A Dfeasibility_pump.py22 def fp_converged(solve_data, config, discrete_only=True): argument
32 def solve_fp_subproblem(solve_data, config): argument
99 def handle_fp_subproblem_optimal(fp_nlp, solve_data, config): argument
127 def fp_loop(solve_data, config): argument
204 def add_orthogonality_cuts(solve_data, config): argument
230 def generate_norm_constraint(fp_nlp, solve_data, config): argument
246 def handle_feas_main_tc(feas_main_results, solve_data, config): argument
H A Dmip_solve.py33 def solve_main(solve_data, config, fp=False, regularization_problem=False): argument
125 def setup_mip_solver(solve_data, config, regularization_problem): argument
177 def handle_main_optimal(main_mip, solve_data, config, update_bound=True): argument
222 def handle_main_other_conditions(main_mip, main_mip_results, solve_data, config): argument
283 def handle_main_infeasible(main_mip, solve_data, config): argument
319 def handle_main_max_timelimit(main_mip, main_mip_results, solve_data, config): argument
359 def handle_main_unbounded(main_mip, solve_data, config): argument
393 def handle_regularization_main_tc(main_mip, main_mip_results, solve_data, config): argument
431 def setup_main(solve_data, config, fp, regularization_problem): argument
H A Dnlp_solve.py28 def solve_subproblem(solve_data, config): argument
116 def handle_nlp_subproblem_tc(fixed_nlp, result, solve_data, config, cb_opt=None): argument
155 def handle_subproblem_optimal(fixed_nlp, solve_data, config, cb_opt=None, fp=False): argument
248 def handle_subproblem_infeasible(fixed_nlp, solve_data, config, cb_opt=None): argument
313 solve_data, config): argument
343 def solve_feasibility_subproblem(solve_data, config): argument
409 def handle_feasibility_subproblem_tc(subprob_terminate_cond, MindtPy, solve_data, config): argument
H A Dsingle_tree.py81 def add_lazy_oa_cuts(self, target_model, dual_values, solve_data, config, opt, argument
158 def add_lazy_affine_cuts(self, solve_data, config, opt): argument
248 def add_lazy_no_good_cuts(self, var_values, solve_data, config, opt, feasible=False): argument
302 def handle_lazy_main_feasible_solution(self, main_mip, solve_data, config, opt): argument
341 def handle_lazy_subproblem_optimal(self, fixed_nlp, solve_data, config, opt): argument
409 def handle_lazy_subproblem_infeasible(self, fixed_nlp, solve_data, config, opt): argument
459 solve_data, config): argument
484 def handle_lazy_regularization_problem(self, main_mip, main_mip_results, solve_data, config): argument
644 def LazyOACallback_gurobi(cb_m, cb_opt, cb_where, solve_data, config): argument
724 def handle_lazy_main_feasible_solution_gurobi(cb_m, cb_opt, solve_data, config): argument
H A Dinitialization.py31 def MindtPy_initialize_main(solve_data, config): argument
107 def init_rNLP(solve_data, config): argument
186 def init_max_binaries(solve_data, config): argument
H A Dcut_generation.py23 def add_oa_cuts(target_model, dual_values, solve_data, config, argument
109 def add_ecp_cuts(target_model, solve_data, config, argument
191 def add_no_good_cuts(var_values, solve_data, config, feasible=False): argument
243 def add_affine_cuts(solve_data, config): argument
H A Diterate.py33 def MindtPy_iteration_loop(solve_data, config): argument
164 def algorithm_should_terminate(solve_data, config, check_cycling): argument
334 def bound_fix(solve_data, config, last_iter_cuts): argument
H A Dutil.py41 def model_is_valid(solve_data, config): argument
98 def calc_jacobians(solve_data, config): argument
162 def var_bound_add(solve_data, config): argument
301 def generate_lag_objective_function(model, setpoint_model, config, solve_data, discrete_only=False): argument
417 def set_solver_options(opt, solve_data, config, solver_type, regularization=False): argument
/dports/math/py-Pyomo/Pyomo-6.1.2/pyomo/contrib/gdpopt/
H A Dnlp_solve.py27 def solve_disjunctive_subproblem(mip_result, solve_data, config): argument
45 def solve_linear_subproblem(mip_model, solve_data, config): argument
95 def solve_NLP(nlp_model, solve_data, config): argument
201 def solve_MINLP(model, solve_data, config): argument
316 def initialize_subproblem(model, solve_data): argument
336 def update_subproblem_progress_indicators(solved_model, solve_data, config): argument
377 def solve_local_NLP(mip_var_values, solve_data, config): argument
407 def solve_local_subproblem(mip_result, solve_data, config): argument
478 def solve_global_subproblem(mip_result, solve_data, config): argument
H A Dmaster_initialize.py21 def GDPopt_initialize_master(solve_data, config): argument
55 def init_custom_disjuncts(solve_data, config): argument
90 def init_fixed_disjuncts(solve_data, config): argument
116 def init_max_binaries(solve_data, config): argument
153 def init_set_covering(solve_data, config): argument
223 def solve_set_cover_mip(model, disj_needs_cover, solve_data, config): argument
H A Dbranch_and_bound.py39 def _perform_branch_and_bound(solve_data): argument
185 def _branch_on_node(node_data, node_model, solve_data): argument
235 def _prescreen_node(node_data, node_model, solve_data): argument
260 def _evaluate_node(node_data, node_model, solve_data): argument
272 def _solve_rnGDP_subproblem(model, solve_data): argument
352 def _solve_local_rnGDP_subproblem(model, solve_data): argument
H A Dcut_generation.py28 def add_subproblem_cuts(subprob_result, solve_data, config): argument
38 def add_outer_approximation_cuts(nlp_result, solve_data, config): argument
144 def add_affine_cuts(nlp_result, solve_data, config): argument
207 def add_integer_cut(var_values, target_model, solve_data, config, feasible=False): argument
H A Diterate.py13 def GDPopt_iteration_loop(solve_data, config): argument
65 def algorithm_should_terminate(solve_data, config): argument
120 def algorithm_is_making_progress(solve_data, config): argument
H A Dmip_solve.py20 def solve_linear_GDP(linear_GDP_model, solve_data, config): argument
189 def solve_LOA_master(solve_data, config): argument
H A Dutil.py79 def presolve_lp_nlp(solve_data, config): argument
114 def process_objective(solve_data, config, move_linear_objective=False, use_mcpp=True, updata_var_co… argument
286 def build_ordered_component_lists(model, solve_data): argument
362 def setup_results_object(solve_data, config): argument
492 def create_utility_block(model, name, solve_data): argument
/dports/math/py-Pyomo/Pyomo-6.1.2/pyomo/contrib/pyros/
H A Dseparation_problem_methods.py351 def is_violation(model_data, config, solve_data): argument
413 def solver_call_separation(model_data, config, solver, solve_data, is_global): argument
H A Dmaster_problem_methods.py285 def solver_call_master(model_data, config, solver, solve_data): argument
/dports/math/libmesh/libmesh-1.6.2/src/solvers/
H A Deigen_time_solver.C114 std::pair<unsigned int, unsigned int> solve_data = in solve() local
/dports/math/libmesh/libmesh-1.6.2/src/systems/
H A Deigen_system.C311 std::pair<unsigned int, unsigned int> solve_data; in solve() local
H A Dcondensed_eigen_system.C152 std::pair<unsigned int, unsigned int> solve_data; in solve() local
/dports/math/py-Pyomo/Pyomo-6.1.2/pyomo/contrib/gdpopt/tests/
H A Dtest_gdpopt.py347 def assert_correct_disjuncts_active(nlp_model, solve_data): argument
558 def assert_correct_disjuncts_active(nlp_model, solve_data): argument
/dports/science/hypre/hypre-2.23.0/src/struct_ls/
H A Dsmg_relax.c51 void **solve_data; /* Array of size `num_spaces' */ member
221 void **solve_data; in hypre_SMGRelax() local
534 void **solve_data; in hypre_SMGRelaxSetupASol() local
/dports/math/py-or-tools/or-tools-9.2/ortools/sat/
H A Dcp_model_lns.h422 virtual void AdditionalProcessingOnSynchronize(const SolveData& solve_data) {} in AdditionalProcessingOnSynchronize()
H A Dcp_model_lns.cc1469 AdditionalProcessingOnSynchronize(const SolveData& solve_data) { in AdditionalProcessingOnSynchronize()