makeZDT6Function {smoof}R Documentation

ZDT6 Function

Description

Builds and returns the two-objective ZDT6 test problem. For mm objective it is defined as follows

f(x)=(f1(x),f2(x))f(\mathbf{x}) = \left(f_1(\mathbf{x}), f_2(\mathbf{x})\right)

with

f1(x)=1exp(4x1)sin6(6πx1),f2(x)=g(x)h(f1(x1),g(x))f_1(\mathbf{x}) = 1 - \exp(-4\mathbf{x}_1)\sin^6(6\pi\mathbf{x}_1), f_2(\mathbf{x}) = g(\mathbf{x}) h(f_1(\mathbf{x}_1), g(\mathbf{x}))

where

g(x)=1+9(i=2mxim1)0.25,h(f1,g)=1(f1(x)g(x))2g(\mathbf{x}) = 1 + 9 \left(\frac{\sum_{i = 2}^{m}\mathbf{x}_i}{m - 1}\right)^{0.25}, h(f_1, g) = 1 - \left(\frac{f_1(\mathbf{x})}{g(\mathbf{x})}\right)^2

and xi[0,1],i=1,,m\mathbf{x}_i \in [0,1], i = 1, \ldots, m. This function introduced two difficulities (see reference): 1. the density of solutions decreases with the closeness to the Pareto-optimal front and 2. the Pareto-optimal solutions are nonuniformly distributed along the front.

Usage

makeZDT6Function(dimensions)

Arguments

dimensions

[integer(1)]
Number of decision variables.

Value

[smoof_multi_objective_function]

References

E. Zitzler, K. Deb, and L. Thiele. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results. Evolutionary Computation, 8(2):173-195, 2000


[Package smoof version 1.6.0.3 Index]