makeED1Function function

ED1 Function

ED1 Function

Builds and returns the multi-objective ED1 test problem.

The ED1 test problem is defined as follows:

Minimize c("\n\n", "f[j](X)=(1/(r(X)+1))p(Theta(X))f[j](X) = (1 / (r(X) + 1)) * p(\\Theta(X))"), for j=1,...,mj = 1, ..., m,

with X=(x[1],...,x[n])X = (x[1], ..., x[n]), where 0x[i]10 \le x[i] \le 1, and Θ=(θ[1],...,θ[m1])\Theta = (\theta[1], ..., \theta[m-1]), where 0θ[j]π/20 \le \theta[j] \le \pi/2, for i=1,...,ni = 1, ..., n and j=1,...,m1j = 1, ..., m - 1.

Moreover r(X)=sqrt(x[m]2+...+x[n]2)r(X) = sqrt(x[m]^2 + ... + x[n]^2),

p[1](Θ)=cos(θ[1])(2/γ)p[1](\Theta) = cos(\theta[1])^(2/\gamma),

p[j](Θ)=(sin(θ[1])...sin(θ[j1])cos(θ[j]))(2/γ)p[j](\Theta) = (sin(\theta[1]) * ... * sin(\theta[j - 1]) * cos(\theta[j]))^(2/\gamma), for 2jm12 \le j \le m - 1,

and p[m](Θ)=(sin(θ[1])...sin(θ[m1]))(2/γ)p[m](\Theta) = (sin(\theta[1]) * ... * sin(\theta[m - 1]))^(2/\gamma).

makeED1Function(dimensions, n.objectives, gamma = 2, theta)

Arguments

  • dimensions: [integer(1)]

    Number of decision variables.

  • n.objectives: [integer(1)]

    Number of objectives.

  • gamma: [numeric(1)]

    Optional parameter. Default is 2, which is recommended by Emmerich and Deutz.

  • theta: [numeric(dimensions)]

    Parameter vector, whose components have to be between 0 and 0.5*pi. The default is theta = (pi/2) * x (with x being the point from the decision space) as recommended by Emmerich and Deutz.

Returns

[smoof_multi_objective_function]

References

M. T. M. Emmerich and A. H. Deutz. Test Problems based on Lame Superspheres. Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization (EMO 2007), pp. 922-936, Springer, 2007.

  • Maintainer: Jakob Bossek
  • License: BSD_2_clause + file LICENSE
  • Last published: 2023-03-10