DTLZ5 Function (family)
Builds and returns the multi-objective DTLZ5 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 DTLZ5 test problem is defined as follows:
Minimize c("\n", "f[1](X)=(1+g(XM))∗cos(theta[1]∗pi/2)∗cos(theta[2]∗pi/2)∗...∗cos(theta[M−2]∗pi/2)∗cos(theta[M−1]∗pi/2)")
Minimize c("\n", "f[2](X)=(1+g(XM))∗cos(theta[1]∗pi/2)∗cos(theta[2]∗pi/2)∗...∗cos(theta[M−2]∗pi/2)∗sin(theta[M−1]∗pi/2)")
Minimize c("\n", "f[3](X)=(1+g(XM))∗cos(theta[1]∗pi/2)∗cos(theta[2]∗pi/2)∗...∗sin(theta[M−2]∗pi/2)")
...
Minimize c("\n", "f[M−1](X)=(1+g(XM))∗cos(theta[1]∗pi/2)∗sin(theta[2]∗pi/2)")
Minimize c("\n", "f[M](X)=(1+g(XM))∗sin(theta[1]∗pi/2)")
with 0<=x[i]<=1, for i=1,2,...,n
where c("\n", "theta[i]=pi/(4∗(1+g(XM)))∗(1+2∗g(XM)∗x[i]),")
for i=2,3,...,(M−1)
and c("\n", "g(XM)=sumx[i]inXM(x[i]−0.5)2")
makeDTLZ5Function(dimensions, n.objectives)
Arguments
Returns
[smoof_multi_objective_function
]
Note
This problem definition does not exist in 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).
Also, note that in case of a bi-objective scenario (n.objectives = 2L
) DTLZ2 and DTLZ5 are identical.
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