Evolutionary Algorithms for Food Science and Technology

Conclusion

There is no doubt that in the domain of food science evolutionary algorithms (EAs) have proven efficient as an optimization tool for single- or multiobjective problems. Our aim with this book is twofold: first, we hope to direct attention to less classical features of EAs, such as cooperative evolution schemes, that allow an optimization problem to be turned into an evolutionary problem in a different, often more computationally efficient way. Human expertise and man–machine interactions are the second topic we aim to showcase in this book. The quantities to be optimized are very difficult to turn into equations, as they are often variable, user-dependent and consider perceptive (taste, flavor), social (sustainability) or expert assessments. We are convinced that interactive evolutionary schemes are a rich ground for developing interactive modeling and decision making.

Let us wrap up this work with a translation of a short story used by Roland Gori to introduce one of his talks. Roland Gori is a psychoanalyst, emeritus professor of psychology at Aix-Marseille university, and specialist in social and psychological issues related to evaluation.

This is the story of two citizens, both named Francis, who live in the same village: one of them is a taxi driver, the other a priest. They die on the same day, and appear before the Lord. Francis the taxi driver comes first. The Lord consults the register and says, “You have deserved Heaven. Here is your argent garment and your ...