1# DAKOTA INPUT FILE - dakota_sbo_illum.in
2
3# Demonstrates the use of approximation models and a trust region
4# optimization environment in the illumination example problem.
5
6environment,
7	graphics
8	method_pointer = 'SBLO'
9
10method,
11	id_method = 'SBLO'
12	surrogate_based_local
13	model_pointer = 'SURROGATE'
14	approx_method_pointer = 'NLP'
15	max_iterations = 100,
16	trust_region
17	  initial_size = 0.10
18	  contraction_factor = 0.50
19	  expansion_factor   = 1.50
20
21method,
22	id_method = 'NLP'
23#	optpp_newton,
24#	optpp_cg,
25#	npsol,
26#	dot_bfgs,
27#	dot_frcg,
28	conmin_frcg
29	  max_iterations = 50,
30	  convergence_tolerance = 1e-8
31
32model,
33	id_model = 'SURROGATE'
34	surrogate global
35	  responses_pointer = 'SURROGATE_RESP'
36	  dace_method_pointer = 'SAMPLING'
37#	  reuse_samples region
38#	  use_derivatives	#s2
39	  correction multiplicative zeroth_order
40#	  neural_network
41#	  polynomial quadratic
42	  gaussian_process surfpack
43	   correlation_lengths =  0.707106781186547 0.707106781186547 0.707106781186547 0.707106781186547 0.707106781186547 0.707106781186547 0.707106781186547	#s0
44           trend constant
45#	  mars
46# 	surogate local taylor_series
47#	  actual_model_pointer = 'TRUTH'
48
49variables,
50        continuous_design = 7
51          initial_point   .5 .5 .5 .5 .5 .5 .5
52          lower_bounds   0. 0. 0. 0. 0. 0. 0.
53          upper_bounds   1. 1. 1. 1. 1. 1. 1.
54          descriptors   'x1' 'x2' 'x3' 'x4' 'x5' 'x6' 'x7'
55
56responses,
57	id_responses = 'SURROGATE_RESP'
58	objective_functions = 1
59 	analytic_gradients
60#  	numerical_gradients
61#  	  method_source dakota
62#  	  interval_type central
63# 	  fd_gradient_step_size = .00001
64#	analytic_hessians
65	no_hessians
66
67###############################################
68# SAMPLING method specifications for building #
69# surrogate functions			      #
70###############################################
71method,
72	id_method = 'SAMPLING'
73	model_pointer = 'TRUTH'
74#	dace box_behnken
75#	dace central_composite
76	dace lhs
77	  seed = 13579
78	  samples = 40
79#	dace oas seed = 5
80#	  samples = 49 symbols = 7
81
82model,
83	id_model = 'TRUTH'
84	single
85	  interface_pointer = 'TRUE_FN'
86	  responses_pointer = 'TRUE_RESP'
87
88interface,
89	direct
90	id_interface = 'TRUE_FN'
91 	  analysis_drivers =    'illumination'
92
93responses,
94	id_responses = 'TRUE_RESP'
95	objective_functions = 1
96#	analytic_gradients		#s2
97	no_gradients			#s0,#s1
98#  	numerical_gradients
99#  	  method_source dakota
100#  	  interval_type central
101#  	  fd_gradient_step_size = .0001
102	no_hessians
103