Hostname: page-component-848d4c4894-x5gtn Total loading time: 0 Render date: 2024-05-14T14:56:35.639Z Has data issue: false hasContentIssue false
  • English
  • Français

An integrated simulation and optimization model of sheep farms as a tool to explore technical and environmental objectives

Published online by Cambridge University Press:  17 February 2015

D. Villalba ,
B. Díez-Unquera ,
A. Carrascal ,
A. Bernués  and
R. Ruiz
D. Villalba*
Affiliation:
University of Lleida, Avda. Rovira Roure 178, 25198 Lleida, Spain
B. Díez-Unquera
Affiliation:
NEIKER-Tecnalia, Arkaute’s Agrifood Campus, PO Box 46, 01080 Vitoria-Gasteiz, Spain
A. Carrascal
Affiliation:
DAIA Intelligent Solutions S.L., Pol. Industrial Mallutz, Pabellón 18, local 5, 20240 Ordizia, Spain
A. Bernués
Affiliation:
CITA, Avda. Montañana 930, 50059 Zaragoza, Spain
R. Ruiz
Affiliation:
NEIKER-Tecnalia, Arkaute’s Agrifood Campus, PO Box 46, 01080 Vitoria-Gasteiz, Spain
*
†E-mail: dvillalba@prodan.udl.es
Get access

Abstract

An abstract is not available for this content so a preview has been provided. Please use the Get access link above for information on how to access this content.
Image of the first page of this content. For PDF version, please use the ‘Save PDF’ preceeding this image.'

Keywords

sheepintegrated modellingmechanistic modelproduction simulation
Type
Full Paper
Information
Advances in Animal Biosciences , Volume 6 , Special Issue 1: Proceedings of the MACSUR International Livestock Modelling and Research Colloquium , March 2015 , pp. 6 - 8
Copyright
© The Animal Consortium 2015 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Agricultural and Food Research Council 1993. Energy and protein requirements of ruminants: an advisory manual prepared by the AFRC Technical Committee on Responses to Nutrients. CAB International, 159pp.Google Scholar
Deb, K, Agrawal, S, Pratap, A and Meyarivan, T 2000. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. Lecture Notes in Computer Science 1917, 849–858.Google Scholar
Díez Unquera, B 2013. Desarrollo de un modelo de simulación y optimización adaptado al ovino lechero. Tesis Doctoral, Universidad de Zaragoza.Google Scholar
Dzakuma, JM and Harris, DL 1989. Computer modeling of sheep reproduction. 1. An algorithm for quantifying anestrous cycles in ewes. Journal of Animal Science 67, 2197–2211.Google Scholar
Fonseca, CM and Fleming, PJ 1993. Genetic algorithms for multiobjective optimization: formulation discussion and generalization. ICGA Proceedings of the 5th International Conference on Genetic Algorithms, 416–423.Google Scholar
Illius, AW and Gordon, IJ 1991. Prediction of intake and digestion in ruminants by a model of rumen kinetics integrating animal size and plant characteristics. Journal of Agricultural Science 116, 145–157.Google Scholar
Mayer, D, Belward, J and Burrage, K 1998. Optimizing simulation models of agricultural systems. Annals of Operations Research 82, 219–232.Google Scholar
Ripoll-Bosch, R, de Boer, IJM, Bernues, A and Vellinga, TV 2013. Accounting for multi-functionality of sheep farming in the carbon footprint of lamb: a comparison of three contrasting Mediterranean systems. Agricultural Systems 116, 60–68.Google Scholar
Ripoll-Bosch, R, Díez-Unquera, B, Ruiz, R, Villalba, D, Molina, E, Joy, M and Bernués, A 2012. An integrated sustainability assessment of Mediterranean sheep farms with different degrees of intensification. Agricultural Systems 105, 46–56.Google Scholar