Authors:
A. L. Márquez
;
F. Manzano-Agugliaro
;
C. Gil
;
R. Cañero-León
;
F. G. Montoya
and
R. Baños
Affiliation:
University of Almeria, Spain
Keyword(s):
MultiObjective optimization, Greenhouse crop distribution, NSGA-II, msPESA, Risk management.
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:
Multiobjective evolutionary algorithms (MOEAs) are known for their ability to optimize several objective functions simultaneously to provide a representative set of the Pareto front, which is a set of problem solutions representing a trade-off between the best values of each one of the objectives. This characteristic is specially interesting for the optimization of many real world problems, such as the allocation of land resources to maximize profit while reducing the economical risks associated to different distributions of crops in southern Spain, which has one of the largest concentrations of greenhouses in the world.