OPTIMIZATION OF REDUCED MODEL OF ORDER TWO OF A GREENHOUSE USING GENETIC ALGORITHMS

The cultures under greenhouse know an important development, challange an increased competing and conditioned market by a strict quality standards.
The process “greenhouses” become considerably sophisticated and so inordinately expensive.
This is why, the “growers’’ who want to remain competitive, must optimize their investment by a great control of the production conditions.
The improvement of climatic management maybe obtained, by coupling between the different components of energy and the water assessment which must be taking into account.
A new method for selecting the parameters based on the genetic algorithm which optimizes the choice of parameters by minimizing a cost function is presented.
The proposed algorithm gives a fast convergence towards the optimal solution.
Genetic algorithms (GAs) are global, parallel, stochastic search methods, founded on Darwinian evolutionary principles The cost function is defined by a small- scale model of ‘second order’ of a horticultural greenhouse.
This model could be employed to simulate and envisage the environment of a hot greenhouse, as well as, the methods of agreement to calculate their parameters.
This study focuses on the dynamic behaviours of the inside air temperature and humidity.
Experimental results were used to validate the on some model.
The data used to compute the simulation models were acquired in an experimental greenhouse using a sampling time interval of one hour.

International Symposium on High Technology for Greenhouse System Management: Greensys2007

M. Hassane, D. Belkacem, B. Fateh

Climate, vapour pressure, optimization, genetic algorithm, greenhouse, climate models, parameters

https://doi.org/10.17660/ActaHortic.2008.801.53