Authors:
Salma Mesmoudi
1
;
Nathalie Perrot
1
;
Romain Reuillon
2
;
Paul Bourgine
2
and
Evelyne Lutton
3
Affiliations:
1
INRA, France
;
2
ISC-PIF, CNRS CREA and UMR 7656, France
;
3
INRIA Saclay - Ile-de-France, France
Keyword(s):
Multiobjective evolutionary algorithm, Viability modeling, Optimal path search, Indirect encoding, Agri-food process modeling, Cheese ripening.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Computational Intelligence
;
Evolutionary Computing
;
Evolutionary Multiobjective Optimization
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
Viability theory is a very attractive theoretical approach for the modeling of complex dynamical systems. However, its scope of application is limited due to the high computational power it necessitates. Evolutionary computation is a convenient way to address some issues related to this theory. In this paper, we present a multiobjective evolutionary approach to address the optimisation problem related to the computation of optimal command profiles of a complex process. The application we address here is a real size problem from dairy industry, the modeling of a Camembert cheese ripening process. We have developed a parallel implementation of a multiobjective EA that has produced a Pareto front of optimal control profiles (or trajectories), with respect to four objectives. The Pareto front was then analysed by an expert who selected a interesting compromise, yielding a new control profile that seems promising for industrial applications.