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📄 output.quadratic.30.log

📁 PostsBayesian Optimization Algorithm with Decision Graphs in C++,
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=============================================== Simple Bayesian Optimization Algorithm in C++ Version 1.0 (Released in March 1999) Copyright (c) 1999 Martin Pelikan Author: Martin Pelikan----------------------------------------------- Parameter values from: input.quadratic.30===============================================Parameter Values:Description                                                Identifier                 Type       Value   ----------------------------------------------------------------------------------------------------------------Size of the population                                     populationSize             long       300The number of parents to select (% from population)        parentsPercentage          float      50.000000Size of offspring to create (% from population)            offspringPercentage        float      50.000000Number of fitness function to use                          fitnessFunction            int        0 (Quadratic 0.9 0 0 1)Size of the problem (of one dimension)                     problemSize                int        30Maximal Number of Generations to Perform                   maxNumberOfGenerations     long       40Maximal Number of Fitness Calls (-1 when unbounded)        maxFitnessCalls            long       -1Termination threshold for the univ. freq. (-1 is ignore)   epsilon                    float      0.010000Stop if the optimum was found?                             stopWhenFoundOptimum       char       0 (No)Percentage of opt. and nonopt. ind. threshold (-1 is ignore) maxOptimal                 float      -1.000000Maximal number of incoming edges in dep. graph for the BOA maxIncoming                int        1Wait for enter after printing out generation statistics?   pause                      char       0Output file name                                           outputFile                 char*      output.quadratic.30Threshold for guidance (closeness to 0,1)                  guidanceThreshold          float      0.300000Random Seed                                                randSeed                   long       123--------------------------------------------------------Generation                   : 0Fitness evaluations          : 300Fitness (max/avg/min)        : (12.400000 7.184000 1.800000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 001111110011001111011100001000--------------------------------------------------------Generation                   : 1Fitness evaluations          : 450Fitness (max/avg/min)        : (12.900000 8.625000 2.800000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111100111110011111111111--------------------------------------------------------Generation                   : 2Fitness evaluations          : 600Fitness (max/avg/min)        : (13.500000 9.948667 4.800000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 110011110011100000111111001111--------------------------------------------------------Generation                   : 3Fitness evaluations          : 750Fitness (max/avg/min)        : (14.700000 11.061333 7.600000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111111000011110011111111--------------------------------------------------------Generation                   : 4Fitness evaluations          : 900Fitness (max/avg/min)        : (14.700000 12.063666 8.700000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111111000011110011111111--------------------------------------------------------Generation                   : 5Fitness evaluations          : 1050Fitness (max/avg/min)        : (14.700000 12.892999 8.500000)Percentage of optima in pop. : 0.00Population bias              : .1............................Best solution in the pop.    : 111111111111000011110011111111--------------------------------------------------------Generation                   : 6Fitness evaluations          : 1200Fitness (max/avg/min)        : (14.799999 13.556666 10.599999)Percentage of optima in pop. : 0.00Population bias              : 11............................Best solution in the pop.    : 111111110011111111001111111111--------------------------------------------------------Generation                   : 7Fitness evaluations          : 1350Fitness (max/avg/min)        : (14.900000 14.146333 11.499999)Percentage of optima in pop. : 0.00Population bias              : 11............................Best solution in the pop.    : 111111001111111111111111111111--------------------------------------------------------Generation                   : 8Fitness evaluations          : 1500Fitness (max/avg/min)        : (14.900000 14.524999 13.999998)Percentage of optima in pop. : 0.00Population bias              : 111111....11....11..11....11..Best solution in the pop.    : 111111001111111111111111111111--------------------------------------------------------Generation                   : 9Fitness evaluations          : 1650Fitness (max/avg/min)        : (15.000000 14.665000 14.200000)Percentage of optima in pop. : 0.33Population bias              : 11111111111111..111111111111..Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 10Fitness evaluations          : 1800Fitness (max/avg/min)        : (15.000000 14.767000 14.400000)Percentage of optima in pop. : 2.33Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 11Fitness evaluations          : 1950Fitness (max/avg/min)        : (15.000000 14.840333 14.499999)Percentage of optima in pop. : 7.33Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 12Fitness evaluations          : 2100Fitness (max/avg/min)        : (15.000000 14.903000 14.699999)Percentage of optima in pop. : 20.67Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 13Fitness evaluations          : 2250Fitness (max/avg/min)        : (15.000000 14.943000 14.699999)Percentage of optima in pop. : 50.00Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 14Fitness evaluations          : 2400Fitness (max/avg/min)        : (15.000000 15.000000 15.000000)Percentage of optima in pop. : 100.00Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111=================================================================FINAL STATISTICSTermination reason           : Bit convergence (with threshold epsilon)Generations performed        : 14Fitness evaluations          : 2400Fitness (max/avg/min)        : (15.000000 15.000000 15.000000)Percentage of optima in pop. : 100.00Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111The End.

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