1#@ s0: UserMan=rosen_opt_sbo
2# DAKOTA INPUT FILE - dakota_sbo_rosen.in
3# Dakota Input File: rosen_opt_sbo.in         #s0
4
5# Surrogate-based optimization to minimize Rosenbrock's function.
6
7# Note on testing in this file:
8# These tests exercise the various surrogate model types that are
9# available in the surrogate based optimization environment. Here, the
10# options are "polynomial," "neural network," "mars,"
11# "gaussian_process surfpack (kriging)," and "taylor_series". See the
12# DAKOTA Users Manual for a description of these surrogate model
13# types.
14
15environment
16  tabular_data
17    tabular_data_file = 'rosen_opt_sbo.dat'   #s0
18  top_method_pointer = 'SBLO'
19
20method
21  id_method = 'SBLO'
22  surrogate_based_local
23    model_pointer = 'SURROGATE'
24    method_pointer = 'NLP'
25    max_iterations = 500
26#	soft_convergence_limit = 10
27###############################################
28# the trust region (TR) commands specify the
29# size of the first trust region, plus the
30# scaling factors that are applied to the TR
31# on subsequent interations
32###############################################
33  trust_region
34    initial_size = 0.10
35    minimum_size = 1.0e-6
36    contract_threshold = 0.25
37    expand_threshold   = 0.75
38    contraction_factor = 0.50
39    expansion_factor   = 1.50
40
41###############################################
42# begin opt specification
43###############################################
44method
45  id_method = 'NLP'
46# output verbose
47  conmin_frcg
48#	optpp_q_newton
49#	npsol_sqp
50#	dot_bfgs
51#	dot_frcg
52    max_iterations = 50
53    convergence_tolerance = 1e-8
54
55model
56  id_model = 'SURROGATE'
57  surrogate global                      #s0,#s1,#s2,#s3,#s4,#s7,#s8,#s9,#s10,#s11
58#	  reuse_samples region
59#	  use_derivatives			#s10,#s11
60    correction additive zeroth_order 		#s0,#s1,#s2,#s3,#s4,#s7,#s8,#s9,#s10,#s11
61### Section to specify surface fit method.
62    polynomial quadratic                #s0
63#	  neural_network			                #s1
64#	    nodes = 10  # to get historical behavior on test 1
65#	  gaussian_process surfpack		        #s2,#s3,#s9,#s10,#s11
66#	   correlation_lengths 0.79 0.76	    #s3
67#	  mars                                #s4
68#	  moving_least_squares			          #s7
69#	  radial_basis				                #s8
70# 	surrogate local taylor_series		    #s5,#s6
71    dace_method_pointer = 'SAMPLING'		#s0,#s1,#s2,#s3,#s4,#s7,#s8,#s9,#s10,#s11
72#	  actual_model_pointer = 'TRUTH' 	    #s5,#s6
73  responses_pointer = 'SURROGATE_RESP'
74
75variables
76  continuous_design = 2
77    initial_point   -1.2  1.0
78    lower_bounds    -2.0 -2.0
79    upper_bounds     2.0  2.0
80    descriptors      'x1' 'x2'
81
82responses
83  id_responses = 'SURROGATE_RESP'
84  objective_functions = 1
85#  analytic_gradients               #s3,#s7,#s8,#s9,#s10,#s11
86  numerical_gradients               #s0,#s1,#s2,#s4,#s5,#s6
87    method_source dakota		        #s0,#s1,#s2,#s4,#s5,#s6
88    interval_type central		        #s0,#s1,#s2,#s4,#s5,#s6
89    fd_step_size = 1.e-6	          #s0,#s1,#s2,#s4,#s5,#s6
90  no_hessians
91
92###############################################
93# Sampling method specifications for sampling in
94# the trust regions of the SBO environment
95###############################################
96method
97  id_method = 'SAMPLING'
98#	dace box_behnken
99#	dace central_composite
100#	dace oas #seed = 5
101#	  samples = 49 symbols = 7
102#	dace lhs #seed = 5
103#	  samples = 10 symbols = 10
104# To switch from the LHS code (used in the
105# sampling method) to DDACE, comment out
106# the four lines below and comment out the two
107# lines starting with 'dace lhs' above.
108  sampling
109    samples = 10          #s0,#s1,#s2,#s3,#s5,#s6,#s7,#s8,#s9,#s10
110#	  samples = 30		      #s4
111#	  samples =  5		      #s11
112    seed = 531
113    sample_type lhs
114    model_pointer = 'TRUTH'
115
116model
117  id_model = 'TRUTH'
118  single
119    interface_pointer = 'TRUE_FN'
120    responses_pointer = 'TRUE_RESP'
121
122interface
123  id_interface = 'TRUE_FN'
124  analysis_drivers = 'rosenbrock'
125    direct
126  deactivate evaluation_cache restart_file
127
128responses
129  id_responses = 'TRUE_RESP'
130  objective_functions = 1
131  no_gradients                      #s0,#s1,#s2,#s3,#s4,#s7,#s8,#s9
132#  analytic_gradients               #s5,#s6,#s10,#s11
133#  numerical_gradients
134#    method_source dakota
135#    interval_type central
136#    fd_gradient_step_size = 1.e-6
137  no_hessians                       #s0,#s1,#s2,#s3,#s4,#s5,#s7,#s8,#s9,#s10,#s11
138#  analytic_hessians	#s6
139