Title: Optimisation of thermal performances in livestock housing design solutions using genetic algorithms

Authors: Maria Elena Menconi; Massimo Chiappini; David Grohmann

Addresses: University of Perugia, Department of Agricultural, Food and Environmental Sciences, Borgo XX Giugno, 74, 06100 Perugia, Italy ' University of Perugia, Department of Agricultural, Food and Environmental Sciences, Borgo XX Giugno, 74, 06100 Perugia, Italy ' University of Perugia, Department of Agricultural, Food and Environmental Sciences, Borgo XX Giugno, 74, 06100 Perugia, Italy

Abstract: Various design elements can affect the energy efficiency of buildings. Usually, parametric analysis does not take into account the interactive effects between the different features in terms of building energy use. Genetic algorithm (GA)-based optimisation approach relies on the evolutionary concept of natural selection to converge on an optimal solution and links together many parameters and several solutions. This methodology is well documented in residential buildings but, so far, few tries were made to extend this process to livestock housing and service facilities. In this paper, genetic algorithms are applied as an optimisation tool to find suitable design solutions in terms of thermal performance. This process is applied to a simple sheepfold model located in Mediterranean climate for a medium-size extensive enterprise. The study analyses only passive design solutions.

Keywords: building energy; optimisation; genetic algorithms; passive solutions; thermal performance; livestock housing design; energy efficiency; livestock buildings; livestock production; sheep farming; Mediterranean; sustainable farming.

DOI: 10.1504/IJSAMI.2015.070748

International Journal of Sustainable Agricultural Management and Informatics, 2015 Vol.1 No.2, pp.142 - 162

Received: 07 May 2014
Accepted: 15 Jul 2014

Published online: 22 Jul 2015 *

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