Recombination. Having selected a set of high performing blouses we can now consider how they should be recombined to form a new child. While a traditional genetic algorithm would stochastically search all combinations over many market generations, we can shortcut that process by algorithmically looking for features that have been historically preferred by our target client segment.
To achieve this, we find statistical regularities between the population of blouses’ attributes (or configurations of attributes) and client feedback. For instance, we can model the relationship between attributes of our existing blouses and client feedback via:
Genetic algorithms (and Koza-style genetic programming) have long been a favorite topic of mine. Integrating GA with fashion was not something that came to mind, but is a very interesting solution.