R: Polynomial mutation.

mutPolynomial {ecr}

R Documentation

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