output.3deceptive.30.log

来自「PostsBayesian Optimization Algorithm wit」· LOG 代码 · 共 160 行

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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.3deceptive.30===============================================Parameter Values:Description                                                Identifier                 Type       Value   ----------------------------------------------------------------------------------------------------------------Size of the population                                     populationSize             long       1000The 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 (Fitness-3 DECEPTIVE)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        2Wait for enter after printing out generation statistics?   pause                      char       0Output file name                                           outputFile                 char*      output.3deceptive.30Threshold for guidance (closeness to 0,1)                  guidanceThreshold          float      0.300000Random Seed                                                randSeed                   long       123--------------------------------------------------------Generation                   : 0Fitness evaluations          : 1000Fitness (max/avg/min)        : (8.800001 5.339900 0.800000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 001001000111100001010000111111--------------------------------------------------------Generation                   : 1Fitness evaluations          : 1500Fitness (max/avg/min)        : (9.100000 6.309100 2.400000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 000111111100001111100111111001--------------------------------------------------------Generation                   : 2Fitness evaluations          : 2000Fitness (max/avg/min)        : (9.500000 7.016600 3.400000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111111111000001000000111--------------------------------------------------------Generation                   : 3Fitness evaluations          : 2500Fitness (max/avg/min)        : (9.500000 7.684000 4.000000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111111111000001000000111--------------------------------------------------------Generation                   : 4Fitness evaluations          : 3000Fitness (max/avg/min)        : (9.600000 8.279900 5.400000)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111111000111111001000111--------------------------------------------------------Generation                   : 5Fitness evaluations          : 3500Fitness (max/avg/min)        : (9.700000 8.762600 6.700001)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111000111111111000111111111000--------------------------------------------------------Generation                   : 6Fitness evaluations          : 4000Fitness (max/avg/min)        : (9.700001 9.012800 8.200001)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111111111000111010111111--------------------------------------------------------Generation                   : 7Fitness evaluations          : 4500Fitness (max/avg/min)        : (9.800000 9.186200 8.400001)Percentage of optima in pop. : 0.00Population bias              : ..............................Best solution in the pop.    : 111111111000111111111111000111--------------------------------------------------------Generation                   : 8Fitness evaluations          : 5000Fitness (max/avg/min)        : (9.900000 9.353900 8.800000)Percentage of optima in pop. : 0.00Population bias              : .....1.11111..................Best solution in the pop.    : 000111111111111111111111111111--------------------------------------------------------Generation                   : 9Fitness evaluations          : 5500Fitness (max/avg/min)        : (9.900000 9.500100 8.700001)Percentage of optima in pop. : 0.00Population bias              : ...1.1111111...111111.........Best solution in the pop.    : 000111111111111111111111111111--------------------------------------------------------Generation                   : 10Fitness evaluations          : 6000Fitness (max/avg/min)        : (10.000000 9.633700 8.900001)Percentage of optima in pop. : 1.00Population bias              : 111111111111...111111111......Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 11Fitness evaluations          : 6500Fitness (max/avg/min)        : (10.000000 9.748000 8.500000)Percentage of optima in pop. : 3.60Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 12Fitness evaluations          : 7000Fitness (max/avg/min)        : (10.000000 9.844700 9.500000)Percentage of optima in pop. : 11.30Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 13Fitness evaluations          : 7500Fitness (max/avg/min)        : (10.000000 9.911500 9.200000)Percentage of optima in pop. : 28.10Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 14Fitness evaluations          : 8000Fitness (max/avg/min)        : (10.000000 9.954300 9.700000)Percentage of optima in pop. : 57.70Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111--------------------------------------------------------Generation                   : 15Fitness evaluations          : 8500Fitness (max/avg/min)        : (10.000000 10.000000 10.000000)Percentage of optima in pop. : 100.00Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111=================================================================FINAL STATISTICSTermination reason           : Bit convergence (with threshold epsilon)Generations performed        : 15Fitness evaluations          : 8500Fitness (max/avg/min)        : (10.000000 10.000000 10.000000)Percentage of optima in pop. : 100.00Population bias              : 111111111111111111111111111111Best solution in the pop.    : 111111111111111111111111111111The End.

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