parameters passed to the genetic hybrid algorithm gha
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Parameters passed to the genetic hybrid algorithm (GHA) parameter - PDF document

Parameters passed to the genetic hybrid algorithm (GHA) parameter = value : accepted values description -------------------------------------------------------------------------------------------------


  1. Parameters passed to the genetic hybrid algorithm (GHA) parameter = value : accepted values description ------------------------------------------------------------------------------------------------- --------------------------------------------- PROJECT_NAME = TRIM_LOSS GET_HESSIAN = FALSE : BOOLEAN calculate Hessian matrix PRINT_HESSIAN = FALSE : BOOLEAN print_level = 1 : integer (0-3) for file output: 0=none 1=function values 2=1+weights+actions 3=debug_print superGA_ITERATIONS = 0 : integer > 0 number iterations in superstructure superMC_ITERATIONS = 3 : integer > 0 superGA_SIBS = 4 : integer > 0 number of siblings in superstructure GA_sibs = 16 : integer > 0 number of siblings GA_iterations = 20 : integer > 0 number of times the GHA is applied to a population GA_runs = 3 : integer > 0 Number of times a new population will be created CALL_FIX = TRUE : BOOLEAN always call fixvalue() dbl_SpaceLimit = 0.75 : real > 0 USE_CONVERGENCE_CRIT = FALSE : BOOLEAN dbl_ConvergenceMean = 0.0001 : real > 0 Convergence criteria Mean dbl_ConvergenceBest = 0.0005 : real > 0 Convergence criteria Best PenaltyFunction = LINEAR : LINEAR, QUADRATIC, CONCAVE, EXPONENTIAL, CONSTANT Penalty function to be used REDUCTION = NONE : NONE, NEUTRAL, FAST, SLOW allow reduction of search space ksi_interval = 5 : integer > 0 Interval for reduction of search space and mut. window LINEMETHOD = 2 : integer (1,2,3) 1:dfp_min+lnsrch, 2:dfp_min+cube_step, 3:newton t_incr = 0 : integer > 0 interval for quadratic/cubic interpolations t_final = 20 : integer > 0 t_slope = 0 : integer > 0 f_incr = 3 : integer > 0 interval for strong mutation in fixvalue()

  2. ADD_HISTORY = FALSE : BOOLEAN freeze history as part of current population all times RCOND_LIMIT = 1000.0 : real GE 0 Limit for reciprocal condition number Min_Penalty = 0.1 : real GE 0 minimum penalty c = 0.3 : real [0.005,0.5] penalty coefficient Running_Mean = 3 : integer > 0 beta = 2.0 : real non-uniformity parameter, (default=2) (Michalewicz [1994]) window = 0.5 : real initial mutation window echo_interval = 1 : integer > 0 number indicating how often iteration result should be echoed to resultfile small_zone = 0 : integer (0/1) number indicating whether a smaller zone will be used in the initialization lower_zone = 0.0 : double upper_zone = 0.0 : double rnd_startpoints = 3000 : integer > 0 rnd_accelerator = 1 : integer (0/1) delta_f_min = 0.0 : double digit indicating the limit value when individuals are considered equal crossover = 4 : integer 0:None, 1:Arithmetic, 2:Permuted, 3:Onepoint, 4:Twopoint, 5:Threepoint, 6:Random mutation = 2 : integer (1) 1:Nonuniform, 2:Gradient diversity_check = 2 : integer (0=NONE/1=STOCHASTIC/2=FIXED) diversity check for stochastic immigration grad_filter = 2.0 : double digit gradient filter (Max Steplength) RANDOMIZE_w = TRUE : BOOLEAN RANDOM_DENSITY = 0 : integer 0:Uniform 1:Normal MC_iterations = 3 : integer if SIM_FLIP=TRUE then > 0 number of Monte Carlo Iterations CHECK_KSI = FALSE : BOOLEAN CHECK_VARIABLES = TRUE : BOOLEAN UPDATEw_in = FALSE : BOOLEAN MUTATE_SIGN = FALSE : BOOLEAN s_incr = 10 : integer > 0 GET_RCOND = TRUE : BOOLEAN

  3. RCOND_ITERATIONS = 300 : integer GE 0 STABLE_GRAD = TRUE : BOOLEAN

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