  This research presents ORUGA, a method that tries to automatically optimize
the readability of any text in English. The core idea behind the method is that
certain factors affect the readability of a text, some of which are
quantifiable (number of words, syllables, presence or absence of adverbs, and
so on). The nature of these factors allows us to implement a genetic learning
strategy to replace some existing words with their most suitable synonyms to
facilitate optimization. In addition, this research seeks to preserve both the
original text's content and form through multi-objective optimization
techniques. In this way, neither the text's syntactic structure nor the
semantic content of the original message is significantly distorted. An
exhaustive study on a substantial number and diversity of texts confirms that
our method was able to optimize the degree of readability in all cases without
significantly altering their form or meaning. The source code of this approach
is available at https://github.com/jorge-martinez-gil/oruga.
