Performs a global optimization of required parameters It will return an object containing:

  • minFunctionValue: The minimum value found for the objetive function
  • optima: Array of Array of values for all the variables where the function reach its minimum value
  • iterations: Number of iterations performed in the process
  • finalState: Internal state allowing to continue optimization (initialState)
direct(objectiveFunction: function, lowerBoundaries: Array, upperBoundaries: Array, options: Object): Object
Parameters
objectiveFunction (function) Function to evaluate. It should accept an array of variables
lowerBoundaries (Array) Array containing for each variable the lower boundary
upperBoundaries (Array) Array containing for each variable the higher boundary
options (Object = {})
Name Description
options.iterations number? Number of iterations.
options.epsilon number? Tolerance to choose best current value.
options.tolerance number? Minimum tollerance of the function.
options.tolerance2 number? Minimum tollerance of the function.
options.initialState Object (default {}}) finalState of previous optimization.
Returns
Object: {finalState, iterations, minFunctionValue}