makeDTLZ7Function: DTLZ7 Function (family)

View source: R/mof.dtlz7.R

makeDTLZ7FunctionR Documentation

DTLZ7 Function (family)

Description

Builds and returns the multi-objective DTLZ7 test problem. This problem can be characterized by a disconnected Pareto-optimal front in the search space. This introduces a new challenge to evolutionary multi-objective optimizers, i.e., to maintain different subpopulations within the search space to cover the entire Pareto-optimal front.

The DTLZ7 test problem is defined as follows:

Minimize f_1(\mathbf{x}) = x_1,

Minimize f_2(\mathbf{x}) = x_2,

\vdots\\

Minimize f_{M-1}(\mathbf{x}) = x_{M-1},

Minimize f_{M}(\mathbf{x}) = (1+g(\mathbf{x}_M)) h(f_1,f_2,\cdots,f_{M-1}, g),

with 0 \leq x_i \leq 1, for i=1,2,\dots,n,

where g(\mathbf{x}_M) = 1 + \frac{9}{|\mathbf{x}_M|} \sum_{x_i\in\mathbf{x}_M} x_i

and h(f_1,f_2,\cdots,f_{M-1}, g) = M - \sum_{i=1}^{M-1}\left[\frac{f_i}{1+g}(1 + sin(3\pi f_i))\right]

Usage

makeDTLZ7Function(dimensions, n.objectives)

Arguments

dimensions

[integer(1)]
Number of decision variables.

n.objectives

[integer(1)]
Number of objectives.

Value

[smoof_multi_objective_function]

Note

Attention: Within the succeeding work of Deb et al. (K. Deb and L. Thiele and M. Laumanns and E. Zitzler (2002). Scalable multi-objective optimization test problems, Proceedings of the IEEE Congress on Evolutionary Computation, pp. 825-830) this problem was called DTLZ6.

References

K. Deb and L. Thiele and M. Laumanns and E. Zitzler. Scalable Multi-Objective Optimization Test Problems. Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, 112, 2001


smoof documentation built on March 31, 2023, 11:48 p.m.