Genetic Algorithm and Direct Search Toolbox

ga

Find the minimum of a function using the genetic algorithm

Syntax

• x = ga(fitnessfun, nvars)
  x = ga(fitnessfun, nvars, options)
  x = ga(problem)
  [x, fval] = ga(...)
  [x, fval, reason] = ga(...)
  [x, fval, reason, output] = ga(...)
  [x, fval, reason, output, population] = ga(...)
  [x, fval, reason, output, population, scores] = ga(...)
  

Description

ga implements the genetic algorithm at the command line to minimize an objective function.

x = ga(fitnessfun, nvars) applies the genetic algorithm to an optimization problem, where fitnessfun is the objective function to minimize and nvars is the length of the solution vector x, the best individual found.

x = ga(fitnessfun, nvars, options) applies the genetic algorithm to an optimization problem, using the parameters in the options structure.

x = ga(problem) finds the minimum for problem, a structure that has three fields:

• fitnessfcn -- Fitness function
• nvars -- Number of independent variables for the fitness function
• options -- Options structure created with gaoptimset

[x, fval] = ga(...) returns fval, the value of the fitness function at x.

[x, fval, reason] = ga(...) returns reason, a string containing the reason the algorithm stops.

[x, fval, reason, output] = ga(...) returns output, a structure that contains output from each generation and other information about the performance of the algorithm. The output structure contains the following fields:

• randstate -- The state of rand, the MATLAB random number generator, just before the algorithm started.
• randnstate -- The state of randn the MATLAB normal random number generator, just before the algorithm started. You can use the values of randstate and randnstate to reproduce the output of ga. See Reproducing Your Results.
• generations -- The number of generations computed
• funccount -- The number of evaluations of the fitness function
• message -- The reason the algorithm terminated. This message is the same as the output argument reason.

[x, fval, reason, output, population] = ga(...) returns matrix population, whose rows are the final population.

[x, fval, reason, output, population, scores] = ga(...) returns scores, the scores of the final population.

Example

• [x fval, reason] = ga(@rastriginsFcn, 10)
  x =
  
    Columns 1 through 7 
  
      0.9977    0.9598    0.0085    0.0097   -0.0274   -0.0173    0.9650
  
    Columns 8 through 10 
  
     -0.0021   -0.0210    0.0065
  
  fval =
  
      3.7456
  
  reason =
  
  generations
  

See Also

gaoptimset, gatool

Alphabetical List of Functions

gaoptimget

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