The concepts of fuzzy sets and genetic algorithms: contrasts and similarities of expectations and development patterns (or would you rather mutate or go fuzzy?)

Fuzzy sets and generic algorithms are two important approaches in the area of soft computing. However, despite some similarities in their research development pattern (such as their reliance on approximate, rather than absolutely precise reasoning, and therefore on solutions to problems which are good but not necessarily optimal), there are nevertheless contrasts which adapts the suitability of each approach to a particular problem environment. This paper analyses those contrasts and similarities, with the hope that if they are better understood it will be easier to employ both approaches complementarily and, therefore, to profit more from the synergetic combination of their strengths in a soft computing context