1#@ s*: Label=FastTest 2#@ s*: Label=AcceptanceTest 3#@ s*: DakotaConfig=HAVE_ACRO 4#@ p*: Label=FastTest 5#@ p*: DakotaConfig=HAVE_ACRO 6#@ p0: MPIProcs=3 CheckOutput='dakota.out.1' 7#@ p1: MPIProcs=3 CheckOutput='dakota.out.1' 8#@ s0: UserMan=textbook_hybrid_strat 9#@ s4: DakotaConfig=HAVE_ROL 10#@ p1: DakotaConfig=HAVE_ROL 11#@ [taxonomy:start] 12#@ s0: [analysis:Optimization] 13#@ s0: [method:GeneticAlgorithm] 14#@ s0: [goal:Global] 15#@ s0: [goal:BoundConstraints] 16#@ s0: [variable:Continuous] 17#@ s0: [model:MultiModal] 18#@ s0: [model:NoDerivatives] 19#@ [taxonomy:end] 20 21# DAKOTA INPUT FILE: dakota_hybrid.in 22# Dakota Input File: textbook_hybrid_strat.in #s0,#s4 23 24# Hybrid optimization on the unconstrained Textbook test problem using 25# 3 optimization methods in sequence: 26# genetic algorithm (in Coliny) 27# coordinate pattern search (in Coliny) 28# nonlinear programming (in OPT++) 29# This provides an initial global search using a derivative-free method, 30# followed by a local search using a derivative-free method, with a final 31# local search using a full Newton method. 32# 33# Version s4 uses ROL instead of OPT++ 34 35environment 36 top_method_pointer = 'HS' 37 38method 39 id_method = 'HS' 40 hybrid sequential 41# iterator_servers = 3 #p0,#p1 42 method_pointer_list = 'GA' 'PS' 'NLP' #s0,#s3,#p0 43# method_pointer_list = 'GA' 'PS' 'PS2' #s1,#s2 44# method_pointer_list = 'GA' 'PS' 'ROL' #s4,#p1 45 46method 47 id_method = 'GA' 48 coliny_ea 49 seed = 1234 50 population_size = 5 51 model_pointer = 'M1' 52# final_solutions = 3 #s3,#p0,#p1 53 final_solutions = 1 #s0,#s1,#s2,#s4 54 output verbose 55 56method 57 id_method = 'PS' 58 coliny_pattern_search 59 stochastic 60 initial_delta = 0.1 61 seed = 1234 62# max_function_evaluations = 100 #s1 63 variable_tolerance = 1e-4 64 solution_target = 1.e-10 65 exploratory_moves 66 basic_pattern 67 model_pointer = 'M1' 68 output verbose 69 70#method, #s1,#s2 71# id_method = 'PS2' #s1,#s2 72# coliny_pattern_search stochastic #s1,#s2 73# max_function_evaluations = 10 #s1,#s2 74# seed = 1234 #s1,#s2 75# initial_delta = 0.1 #s1,#s2 76# variable_tolerance = 1.e-4 #s1,#s2 77# solution_target = 1.e-10 #s1,#s2 78# exploratory_moves basic_pattern #s1,#s2 79# model_pointer = 'M1' #s1,#s2 80# output verbose #s1,#s2 81 82method #s0,#s3,#p0 83 id_method = 'NLP' #s0,#s3,#p0 84 optpp_newton #s0,#s3,#p0 85 gradient_tolerance = 1.e-12 #s0,#s3,#p0 86 convergence_tolerance = 1.e-15 #s0,#s3,#p0 87 model_pointer = 'M2' #s0,#s3,#p0 88 output verbose #s0,#s3,#p0 89 90#method #s4,#p1 91# id_method = 'ROL' #s4,#p1 92# rol #s4,#p1 93# gradient_tolerance 1.0e-8 #s4,#p1 94# constraint_tolerance 1.0e-8 #s4,#p1 95# variable_tolerance 1.0e-8 #s4,#p1 96# model_pointer = 'M2' #s4,#p1 97# output verbose #s4,#p1 98 99model 100 id_model = 'M1' 101 single 102 interface_pointer = 'I1' #s0,#s4 103 variables_pointer = 'V1' #s0,#s4 104 responses_pointer = 'R1' 105 106model 107 id_model = 'M2' 108 single 109 interface_pointer = 'I1' #s0,#s4 110 variables_pointer = 'V1' #s0,#s4 111 responses_pointer = 'R2' 112 113variables 114 id_variables = 'V1' #s0,#s4 115 continuous_design = 2 116 initial_point 0.6 0.7 117 upper_bounds 5.8 2.9 118 lower_bounds 0.5 -2.9 119 descriptors 'x1' 'x2' 120 121interface 122 id_interface = 'I1' #s0,#s4 123 analysis_drivers = 'text_book' 124 direct #s0,#s1,#s3,#s4,#p0,#p1 125# system asynch #s2 126 127responses 128 id_responses = 'R1' 129 objective_functions = 1 130 no_gradients 131 no_hessians 132 133responses 134 id_responses = 'R2' 135 objective_functions = 1 136 analytic_gradients 137 analytic_hessians 138