mutPolynomial: Polynomial mutation.

In ecr: Evolutionary Computation in R

Polynomial mutation.

Description

Performs an polynomial mutation as used in the SMS-EMOA algorithm. Polynomial mutation tries to simulate the distribution of the offspring of binary-encoded bit flip mutations based on real-valued decision variables. Polynomial mutation favors offspring nearer to the parent.

Usage

mutPolynomial(ind, p = 0.2, eta = 10, lower, upper)

Arguments

ind	[numeric] Numeric vector / individual to mutate.
p	[numeric(1)] Probability of mutation for each gene of an offspring. In other words, the probability that the value (allele) of a given gene will change. Default is 0.2
eta	[numeric(1) Distance parameter to control the shape of the mutation distribution. Larger values generate offspring closer to the parents. Default is 10.
lower	[numeric] Vector of minimal values for each parameter of the decision space. Must have the same length as ind.
upper	[numeric] Vector of maximal values for each parameter of the decision space. Must have the same length as ind.

Value

[numeric]

References

[1] Deb, Kalyanmoy & Goyal, Mayank. (1999). A Combined Genetic Adaptive Search (GeneAS) for Engineering Design. Computer Science and Informatics. 26. Retrieved from http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.27.767&rep=rep1&type=pdf

See Also

Other mutators: mutBitflip(), mutGauss(), mutInsertion(), mutInversion(), mutJump(), mutScramble(), mutSwap(), mutUniform()

ecr documentation built on March 31, 2023, 10:07 p.m.