BUG: SDBL alignment relies on uniform distribution instead of logistic

[vkhodygo]

See original research.

SBDLAlignment class used to use the same RNG (see also #26) as SBDAlignment for generation of random numbers before and even now in v5.0.0. This is incorrect, SBDLAlignment must rely on the conventional logistic distribution.

[vkhodygo]

Correction: the original source is inconsistent as well. The text says:

r_i that is drawn from a logistic distribution

Whereas the Algorithm 6 states:

r_i ← a random number from uniform distribution (0,1)

This looks like some sort of a copy-paste error to me. The logistic distribution is bounded meaning 1 / r - 1 is bounded as well resulting in finite values of log(1 / r - 1) whereas this is not the case for the uniform distribution (0, 1). However, the uniform distribution is strictly positive as opposed to the logistic one that is defined on the whole R.

Note, that the original paper makes a clear distinction between open and closed intervals such as (0, 1) and [0, 1]. That means using the default rng generating values in the range [0, 1) is incorrect even in the case of SBDAlignment.