copulaedas (version 1.2.1)

edaOptimize: Local Optimization Methods

Description

Methods for the edaOptimize generic function.

Usage

edaOptimizeDisabled(eda, gen, pop, popEval, f, lower, upper)

Arguments

eda

EDA instance.

gen

Generation.

pop

Matrix with one row for each solution in the population.

popEval

Vector with the evaluation of each solution in pop.

f

Objective function

lower

Lower bounds of the variables of the objective function.

upper

Upper bounds of the variables of the objective function.

Value

• A list with the following components.
• pop
  Matrix with one row for each solution in the optimized population.
• popEval
  Vector with the evaluation of each solution in pop.

Details

Local optimization methods improve the solutions sampled by the search distribution. These methods can also be used to implement repairing strategies for constrained problems where the simulated solutions may be unfeasible and some strategy to repair these solutions is available.

The following local optimization methods are implemented.

[object Object]

References

Gonz�lez-Fern�ndez Y and Soto M (2012). copulaedas: An R Package for Estimation of Distribution Algorithms Based on Copulas. Preprint http://arxiv.org/abs/1209.5429{arXiv:1209.5429 [cs.NE]}.