output.3deceptive.30.log

贝叶斯优化算法是一种新的演化算法

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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
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 Parameter values from: input.3deceptive.30
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Parameter Values:

Description                                                Identifier                 Type       Value   
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Size of the population                                     populationSize             long       1000
The number of parents to select (% from population)        parentsPercentage          float      50.000000
Size of offspring to create (% from population)            offspringPercentage        float      50.000000

Number of fitness function to use                          fitnessFunction            int        0 (Fitness-3 DECEPTIVE)
Size of the problem (of one dimension)                     problemSize                int        30

Maximal Number of Generations to Perform                   maxNumberOfGenerations     long       40
Maximal Number of Fitness Calls (-1 when unbounded)        maxFitnessCalls            long       -1
Termination threshold for the univ. freq. (-1 is ignore)   epsilon                    float      0.010000
Stop if the optimum was found?                             stopWhenFoundOptimum       char       0 (No)
Percentage of opt. and nonopt. ind. threshold (-1 is ignore) maxOptimal                 float      -1.000000

Maximal number of incoming edges in dep. graph for the BOA maxIncoming                int        2

Wait for enter after printing out generation statistics?   pause                      char       0

Output file name                                           outputFile                 char*      output.3deceptive.30
Threshold for guidance (closeness to 0,1)                  guidanceThreshold          float      0.300000

Random Seed                                                randSeed                   long       123
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Generation                   : 0
Fitness evaluations          : 1000
Fitness (max/avg/min)        : (8.800001 5.339900 0.800000)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 001001000111100001010000111111
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Generation                   : 1
Fitness evaluations          : 1500
Fitness (max/avg/min)        : (9.100000 6.309100 2.400000)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 000111111100001111100111111001
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Generation                   : 2
Fitness evaluations          : 2000
Fitness (max/avg/min)        : (9.500000 7.016600 3.400000)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 111111111111111000001000000111
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Generation                   : 3
Fitness evaluations          : 2500
Fitness (max/avg/min)        : (9.500000 7.684000 4.000000)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 111111111111111000001000000111
--------------------------------------------------------
Generation                   : 4
Fitness evaluations          : 3000
Fitness (max/avg/min)        : (9.600000 8.279900 5.400000)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 111111111111000111111001000111
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Generation                   : 5
Fitness evaluations          : 3500
Fitness (max/avg/min)        : (9.700000 8.762600 6.700001)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 111000111111111000111111111000
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Generation                   : 6
Fitness evaluations          : 4000
Fitness (max/avg/min)        : (9.700001 9.012800 8.200001)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 111111111111111000111010111111
--------------------------------------------------------
Generation                   : 7
Fitness evaluations          : 4500
Fitness (max/avg/min)        : (9.800000 9.186200 8.400001)
Percentage of optima in pop. : 0.00
Population bias              : ..............................
Best solution in the pop.    : 111111111000111111111111000111
--------------------------------------------------------
Generation                   : 8
Fitness evaluations          : 5000
Fitness (max/avg/min)        : (9.900000 9.353900 8.800000)
Percentage of optima in pop. : 0.00
Population bias              : .....1.11111..................
Best solution in the pop.    : 000111111111111111111111111111
--------------------------------------------------------
Generation                   : 9
Fitness evaluations          : 5500
Fitness (max/avg/min)        : (9.900000 9.500100 8.700001)
Percentage of optima in pop. : 0.00
Population bias              : ...1.1111111...111111.........
Best solution in the pop.    : 000111111111111111111111111111
--------------------------------------------------------
Generation                   : 10
Fitness evaluations          : 6000
Fitness (max/avg/min)        : (10.000000 9.633700 8.900001)
Percentage of optima in pop. : 1.00
Population bias              : 111111111111...111111111......
Best solution in the pop.    : 111111111111111111111111111111
--------------------------------------------------------
Generation                   : 11
Fitness evaluations          : 6500
Fitness (max/avg/min)        : (10.000000 9.748000 8.500000)
Percentage of optima in pop. : 3.60
Population bias              : 111111111111111111111111111111
Best solution in the pop.    : 111111111111111111111111111111
--------------------------------------------------------
Generation                   : 12
Fitness evaluations          : 7000
Fitness (max/avg/min)        : (10.000000 9.844700 9.500000)
Percentage of optima in pop. : 11.30
Population bias              : 111111111111111111111111111111
Best solution in the pop.    : 111111111111111111111111111111
--------------------------------------------------------
Generation                   : 13
Fitness evaluations          : 7500
Fitness (max/avg/min)        : (10.000000 9.911500 9.200000)
Percentage of optima in pop. : 28.10
Population bias              : 111111111111111111111111111111
Best solution in the pop.    : 111111111111111111111111111111
--------------------------------------------------------
Generation                   : 14
Fitness evaluations          : 8000
Fitness (max/avg/min)        : (10.000000 9.954300 9.700000)
Percentage of optima in pop. : 57.70
Population bias              : 111111111111111111111111111111
Best solution in the pop.    : 111111111111111111111111111111
--------------------------------------------------------
Generation                   : 15
Fitness evaluations          : 8500
Fitness (max/avg/min)        : (10.000000 10.000000 10.000000)
Percentage of optima in pop. : 100.00
Population bias              : 111111111111111111111111111111
Best solution in the pop.    : 111111111111111111111111111111

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FINAL STATISTICS
Termination reason           : Bit convergence (with threshold epsilon)
Generations performed        : 15
Fitness evaluations          : 8500
Fitness (max/avg/min)        : (10.000000 10.000000 10.000000)
Percentage of optima in pop. : 100.00
Population bias              : 111111111111111111111111111111
Best solution in the pop.    : 111111111111111111111111111111

The End.