1#@ s*: Label=FastTest
2#@ s0: DakotaConfig=HAVE_NPSOL
3#@ s5: DakotaConfig=HAVE_NPSOL
4#@ s3: DakotaConfig=HAVE_DOT
5#@ s8: DakotaConfig=HAVE_DOT
6#@ s4: DakotaConfig=HAVE_NLPQL
7#@ s9: DakotaConfig=HAVE_NLPQL
8#@ s0: UserMan=textbook_opt_multiobj1
9#@ [taxonomy:start]
10#@ s0: [analysis:Optimization]
11#@ s0: [method:SQP]
12#@ s0: [goal:Local]
13#@ s0: [goal:BoundConstraints]
14#@ s0: [variable:Continuous]
15#@ s0: [model:Smooth]
16#@ s0: [model:FirstDerivatives]
17#@ [taxonomy:end]
18
19# DAKOTA INPUT FILE - dakota_multiobj1.in
20# Dakota Input File: textbook_opt_multiobj1.in            #s0
21
22# Unconstrained multiobjective optimization using the Textbook problem.
23#
24# The formulation is: minimize F
25#                     s.t. x_l <= x <= x_u
26#
27# where F  = w1*f1 + w2*f2 + w3*f3
28#       f1 = original textbook objective fcn
29#       f2 = original textbook constraint 1
30#       f3 = original textbook constraint 2
31
32environment
33  tabular_data
34    tabular_data_file = 'textbook_opt_multiobj1.dat'	#s0
35
36method
37## (NPSOL requires a software license; if not available, try	      #s0
38## conmin_frcg or optpp_q_newton instead)     			      #s0
39  npsol_sqp         #s0,#s5
40#  optpp_newton			#s1,#s6
41#  conmin_frcg			#s2,#s7
42#  dot_bfgs				  #s3,#s8
43#  nlpql_sqp				#s4,#s9
44    convergence_tolerance = 1.e-8
45
46variables
47  continuous_design = 2
48    initial_point    0.9    1.1
49    upper_bounds     5.8    2.9
50    lower_bounds     0.5   -2.9
51    descriptors      'x1'   'x2'
52
53interface
54  analysis_drivers = 'text_book'
55    direct
56
57responses
58  objective_functions = 3
59#    sense = "min" "max" "max"      #s5,#s6,#s7,#s8,#s9
60  weights = .7 .2 .1
61#  weights = .333 .333 .333
62  analytic_gradients
63#  numerical_gradients
64#    method_source vendor
65#    interval_type forward
66#    fd_gradient_step_size = 1.e-6
67  no_hessians                       #s0,#s2,#s3,#s4,#s5,#s7,#s8,#s9
68#  analytic_hessians			          #s1,#s6
69