International Journal of Advanced and Applied Sciences

Int. j. adv. appl. sci.

EISSN: 2313-3724

Print ISSN: 2313-626X

Volume 4, Issue 4  (April 2017), Pages:  58-66


Title: Modeling for development of simulation tool: Cattle diet formulation

Author(s):  Pratiksha Saxena *, Neha Khanna

Affiliation(s):

Department of Applied Mathematics, Gautam Buddha University, Greater Noida, 201308, India

https://doi.org/10.21833/ijaas.2017.04.010

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Abstract:

This paper presents algorithms for simulation tool development to formulate and compute cattle diet at different stages of livestock. Algorithms are proposed for bi-criteria models. The objectives taken are minimization of cost and maximization of the shelf life of animal feed mix. Other objectives achieved by these algorithms are inclusion of nutrient variability in the feed mix and minimization of the deviations. For developing the algorithms, combination of three mathematical programming techniques: linear, stochastic and goal programming is used. Computational and technological interface is included in the field of animal diet formulation by developing the algorithms, which provides better and faster results. Twenty mathematical models are solved by proposed algorithms and obtained results showed superiority of algorithm 2 in terms of nutrient variability whereas algorithm 1 provides better results in terms of lesser cost and more shelf life. Algorithm 3 is taking the two objectives in parallel and providing the optimal feed mix at minimum deviations from the target values of the cost and the shelf life. 

© 2017 The Authors. Published by IASE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Livestock feed, Bi-criteria decision making, Linear programming, Stochastic programming, Goal programming

Article History: Received 18 December 2016, Received in revised form 16 March 2017, Accepted 20 March 2017

Digital Object Identifier: 

https://doi.org/10.21833/ijaas.2017.04.010

Citation:

Saxena P and Khanna N (2017). Modeling for development of simulation tool: Cattle diet formulation. International Journal of Advanced and Applied Sciences, 4(4): 58-66

http://www.science-gate.com/IJAAS/V4I4/Saxena.html


References:

Abayomi OO, Adewale AO, Odianosen EF, and Oyelayo O (2016). A multi criteria productivity analysis for animal feed formulation problem: A case study of Nigerian feed mill industry. International Journal of Innovative Research in Science, Engineering and Technology, 5(1): 647-663.
Anderson AM and Earle MD (1983). Diet planning in the third world by linear and goal programming. Journal of the Operational Research Society, 34(1): 9-16.
https://doi.org/10.1057/jors.1983.2
Hasan NA, Khodary IE, and Dahab MY (2015). Developing a generic decision support system for poultry feeding. International Journal of Advances in Engineering Sciences, 5(3): 32-37.
Nath T and Talukdar A (2014). Linear programming technique in fish feed formulation. International Journal of Engineering Trends and Technology, 17(3): 132-135.
https://doi.org/10.14445/22315381/IJETT-V17P227
NRC (2001). Nutrient requirements of dairy cattle. National Research Council, National Academies Press, Washington, DC, USA.
Prišenk J, Pažek K, Rozman Č, Turk J, and Borec A (2013a). Mathematical method for formulating animal feed rations. Lucrări Științifice-Universitatea de Științe Agricole și Medicină Veterinară, Seria Zootehnie, 59(18): 72-76.
Prišenk J, Pažek K, Rozman Č, Turk J, Janžekovič M, and Borec A (2013b). Application of weighted goal programming in the optimization of rations for sport horses. Journal of Animal and Feed Sciences, 22: 335–341.
https://doi.org/10.22358/jafs/65922/2013
Rehman T and Romero C (1984). Multiple- criteria decision making technique and their role in livestock formulation. Agricultural Systems, 15(1): 23-49.
https://doi.org/10.1016/0308-521X(84)90016-7
Rehman T and Romero C (1987). Goal programming with penalty functions and livestock ration formulation. Agricultural Systems, 23(2): 117-132.
https://doi.org/10.1016/0308-521X(87)90090-4
Romero C and Rehman T (1984). A note on diet planning in the third world by linear and goal programming. Journal of the Operational Research Society, 35(6): 555–558.
https://doi.org/10.1057/jors.1984.108
Sahman MA, Altun AA, Dundar AO, and Yasar A (2015). Solution of mixture problem prioritized raw materials using mixed integer linear programming. International Journal of Advanced Research in Engineering, 1(3): 26-31.
Saxena P (2006). Application of nonlinear programming in the field of animal nutrition: A problem to maximize the weight gain in sheep. National Academy Science Letters, 29(1-2): 59-64.
Saxena P (2011). Comparison of linear and nonlinear programming techniques for animal diet. Applied Mathematics, 1(2): 106-108.
https://doi.org/10.5923/j.am.20110102.17
Saxena P and Chandra M (2011). Animal diet formulation models: A Review (1950-2010). In: Hemming D (Ed.), Animal Science Reviews: 189-197. CAB International, Oxfordshire, UK.
Saxena P and Khanna N (2014a). Animal diet formulation: mathematical programming techniques. CAB Reviews: Perspectives in Agriculture, Veterinary Science Nutrition and Natural Resources, 9(35): 1-12.
Saxena P and Khanna N (2014b). Formulation and computation of cattle feed mix by using TORA and LINGO: Minimization of adverse effect of nutrient ingredient. In the Innovative Applications of Computational Intelligence on Power, Energy and Controls with their Impact on Humanity (CIPECH '14), IEEE, KIET, Ghaziabad, Uttar Pradesh, India: 505-510. https://doi.org/10.1109/CIPECH.2014.7019102
Saxena P and Khanna N (2015a). Formulation and computation of Animal Feed Mix: Optimization by combination of mathematical programming. In the Intelligent Systems and Computing for Bridging the Future- Proceedings of the 49th Annual Convention of the Computer Society of India (CSI), Springer International Publishing, Greater Noida, India: 1: 621-629. https://doi.org/ 10.1007/978-3-319-13728-5_70
Saxena P and Khanna N (2015b). Computation of cattle feed mix by using priority function: Weighted goal programming. In the 2nd International Conference on Computing for Sustainable Global Development, IEEE, New Delhi, India: 1595-1600.
Saxena P and Khanna N (2015c). Optimization of dairy cattle feed by nonlinear programming. In the 2nd International Conference on Computing for Sustainable Global Development, IEEE, New Delhi, India: 1579-1584.
Tozer PR (2000). Least cost ration formulations for Holstein dairy Heifers by using linear and stochastic programming. Journal of dairy science, 83(3): 443-451.
https://doi.org/10.3168/jds.S0022-0302(00)74901-0
Waugh FV (1951). The minimum cost dairy feed. Journal of Farm Economics, 33(3): 299-310.
https://doi.org/10.2307/1233608
Žgajnar J and Kavčič S (2009). Multi-goal pig ration formulation; mathematical optimization approach. Agronomy Research, 7(2): 775-782.
Zoran B and Tunjo P (2011). Optimization of livestock feed blend by use of goal programming. International journal of production economics, 130(2): 218-223.
https://doi.org/10.1016/j.ijpe.2010.12.016