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