Cooperative Coevolution for Agrifood Process Modeling

Abstract

On the contrary to classical schemes of evolutionary optimisations algorithms, single population Cooperative Co-evolution techniques (CCEAs, also called "Parisian" approaches) make it possible to represent the evolved solution as an aggregation of several individuals (or even as a whole population). In other words, each individual represents only a part of the solution. This scheme allows simulating the principles of Darwinian evolution in a more economic way, which results in gain in robustness and efficiency. The counterpart however is a more complex design phase. In this chapter, we detail the design of efficient CCEAs schemes on two applications related to the modeling of an industrial agri-food process. The experiments correspond to complex optimisations encountered in the modeling of a Camembert-cheese ripening process. Two problems are considered:• A deterministic modeling problem, phase prediction, for which a search for a closed form tree expression is performed using genetic programming (GP).• A Bayesian network structure estimation problem. The novelty of the proposed approach is based on the use of a two step process based on an intermediate representation called independence model. The search for an independence model is formulated as a complex optimisation problem, for which the CCEA scheme is particularly well suited. A Bayesian network is finally deduced using a deterministic algorithm, as a representative of the equivalence class figured by the independence model.

A complex system approach to address world challenges in food and agriculture

“…of an economic nature, including product development processes and innovation processes (Bonabeau & Meyer, 2001;Frenken, 2006). Some recently developed tools to address and picture emerging structures at that level are described in the literature (Chavalarias & Cointet, 2008)An interesting example on optimisation of cheese ripening has been described, which includes aspects on quantitative material science and qualitative knowledge of process operators (Barrière et al, 2013;Baudrit, Sicard, Wuillemin, & Perrot, 2010;Perrot, Trelea, Baudrit, Trystram, & Bourgine, 2011)The role of computer science and the description of digital systems for business conduction is nicely addressed (Razavi, Moschoyiannis, & Krause, 2009). In regards to issues of economy and food scarcity, some important aspects are addressed recently (Lagi, Bertrand, & Bar-yam, 2011).…”