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Setting parameters in the Genetic algorithm

The default parameters in GA should be adequate for most problems. However, if the user needs to explore different methods, the following parameters may be set for GA.


Population Size Population size
Number of Generations Number of generations
Selection Operator Selection operator: Tourament, Roullette, SUS
Tournament Size
Tournament size for tournament selection operator
Switch elitism for single objective GA
Number of Elites
Number of elites passed to next generation
Encoding variable
Type of encoding for a variable: Binary=1, Real=2
Numbits variable
Number of bits assigned to a binary variable
Crossover type
Type of real crossover: SBX, BLX
Crossover probability
Real crossover probability
Alpha value for BLX Value of α for BLX operator
Crossover distribution
Distribution index for SBX crossover operator
Mutation probability
Mutation probability in real-space
Mutation distribution
Distribution index for mutation operator
Algorithm Subtype Mulit-objective optimization algorithm: NSGA II, SPEA II
Restart Interval
Frequency of writing restart file for direct GA For multi-objective problems, this parameter governs the frequency of writing TradeOff files
Max Repeat Optimum/Generations Maximum number of generations allowed to repeat as a fraction of the totla number of generations allowed.
Constraint Handling
Constraint handling types: Deb Efficient Constraint Handling, Penalty