Optimization of Greenhouse Climate Model Parameters Using Particle Swarm Optimization and Genetic Algorithms

In the world, the greenhouse culture is getting more and more developed to meet the needs of a more competitive market that is conditioned by very strict norms of quality. Greenhouse production systems are getting highly sophisticated but extremely expensive. That is the reason why the greenhousers, who want to be competitive must optimize their investments thanks to strict production conditions. Nowadays, it is commonly admitted that the decisions related to the management of a greenhouse can be classified into different levels, starting from the on –line control, through the optimization of the environment, to the seasonal planning of the behaviour of the agriculture. The main purpose of our work is to optimize the physical sizes of a reduced model of a greenhouse under Mediterranean conditions. Thus, we use a digital simulation based genetic algorithm (GA) and a particle swarm optimization (PSO). The design goal is successfully achieved using the PSO and compared with that obtained using the GA. For the problem at hand, it is found that the PSO outperforms the GA in some of the presented design cases.