Table 1 Notations.

From: Population diversity control based differential evolution algorithm using fuzzy system for noisy multi-objective optimization problems

\(\varepsilon\)

Noise

\({\sigma }^{2}\)

Noise strength

\(I\)

Identity matrix

\(CR\)

Crossover rate

\(NP\)

Population size

\(F\)

Scaling Factor

\(LE\)

Learning period

\(popdiversity\)

Population diversity

\(refdiversity\)

Reference diversity

\(CRm\)

Crossover rate mean

\({\lambda }_{res}\)

Resampling ratio

\({N}_{re}\)

count of solutions to be resampled

\({f}_{pro}\)

probabilistic based rounding function

\(d\)

Problem dimension

\(s\)

Noise strength

\(\theta\)

Acceptance threshold

\({LS}_{Int}\)

Local search interval

\({LS}_{Feval}\)

Local search number of function evaluations