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GEAOPT = tbx3steadyga

ToolBoX function to define parameters for the Steady State Genetic Algorithm (SSGA) This function defines parameters for the Steady State Genetic Algorithm (SSGA). The special feature of the staedy state GA is the small number of offspring per generation. A large part of the population survives to the next generation unchanged. Often only 2 or 4 individuals are produced each generation. Here 2 individuals are produced (GenerationGap is 2% of 100 individuals). But even a generation gap of 10-20% is still a small number. Because of the small number of new offspring each generation the number of generations must be proportionally larger. Here 10000 generations are used as termination criteria. Recombination/Crossover uses discrete recombination and a recombination/crossover probability of 1.0. For mutation real mutation is used. The mutation probability (default is 1) is internally divided by the number of (internal) variables, thus only one value per individual is mutated. (The used internal value is presented on the screen at the beginning of the optimization.) Just one panmictic population is used. This parameter setting function is provided to show you how to define very well known genetic algorithm using the GEATbx. You can combine the power of the steady state GA with the power of multiple populations (just define multiple subpopulation, here 4 subpopulations with 25 individuals each), the use of different strategies (just define different parameters for the subpopulations, here different mutation range) and competing subpopulations (just set Migration and Competition to on, load of parameters from tbx3comp). However, when using 2 new offspring each generation, competition does not make sence (as each subpopulation still produces only 2 offspring each generation). Thus, competition is not switched on. In this case the optimization must end after 2500 (10000 generations divided by 4 subpopulation, as each subpopulation produces 2 individuals each generation for a total of 8 individuals compared to 2 individuals in the panmictic population case above). See the end of the function for the complete parameter definition. As this "extended" EA is more powerful than the "standard" steady state GA I leave the "extended" parameters settings switched on by default. If you want to switch them off, just set MultiPop = 0 in the source code. Syntax: GEAOPT = tbx3steadyga Input parameter: no input parameters Output parameter: GEAOPT - Structure with newly defined options See also: geamain2, geaoptset, tbx3bin, tbx3real, tbx3comp

This function calls | |
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GEATbx: |
Main page Tutorial Algorithms M-functions Parameter/Options Example functions www.geatbx.com |

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The Genetic and Evolutionary Algorithm Toolbox is