ga:

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   GA run a genetic algorithm.

   Since version 7.
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   Form:
   [x,endPop,bPop,traceInfo]=ga(bounds,evalFN,evalOps,startPop,opts,
                                       termFN,termOps,selectFN,selectOps,
                                       xOverFNs,xOverOps,mutFNs,mutOps)
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   ------
   Inputs
   ------
   bounds         a matrix of upper and lower bounds on the variables
   evalFN         the name of the evaluation .m function
   evalOps        options to pass to the evaluation function ([NULL])
   startPop       a matrix of solutions that can be initialized
                  from initialize.m
   opts           [epsilon prob_ops display] change required to consider two 
                  solutions different, prob_ops 0 if you want to apply the
                  genetic operators probabilisticly to each solution, 1 if
                  you are supplying a deterministic number of operator
                  applications and display is 1 to output progress 0 for
                  quiet. ([1e-6 1 0])
   termFN         name of the .m termination function (['maxGenTerm'])
   termOps        options string to be passed to the termination function
                  ([100]).
   selectFN       name of the .m selection function (['normGeomSelect'])
   selectOpts     options string to be passed to select after
                  select(pop,#,opts) ([0.08])
   xOverFNS       a string containing blank seperated names of Xover.m
                  files (['arithXover heuristicXover simpleXover']) 
   xOverOps       A matrix of options to pass to Xover.m files with the
                  first column being the number of that xOver to perform
                  similiarly for mutation ([2 0;2 3;2 0])
   mutFNs         a string containing blank seperated names of mutation.m 
                  files (['boundaryMutation multiNonUnifMutation ...
                           nonUnifMutation unifMutation'])
   mutOps         A matrix of options to pass to Xover.m files with the
                  first column being the number of that xOver to perform
                  similiarly for mutation ([4 0 0;6 100 3;4 100 3;4 0 0])

   -------
   Outputs
   -------
   x              the best solution found during the course of the run
   endPop         the final population 
   bPop           a trace of the best population
   traceInfo      a matrix of best and means of the ga for each generation

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Children:

Sail: GAOT/b2f
Sail: GAOT/calcbits
Sail: GAOT/initializega
Sail: GAOT/parse