Skip to main content

Advertisement

SpringerLink
Log in

New opportunities in operations research to improve pork supply chain efficiency

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

The structure of the pork sector in world economy is changing. In many countries the number of pig farms is being reduced, while the herd size of the remaining ones is increasing. Pig production process is partitioned into different phases with specialized farms devoted to piglet production, rearing or fattening pigs are common instead of old farrowing-to-fattening farms. Pig farms have tended to be integrated and coordinate their operations into pork supply chains by using tighter vertical coordination linkages. This paper presents a description of the pork supply chain, stressing the role of pig farming as one of the key issues to improve pork supply chain efficiency. A survey of literature to support the decision making on the pork sector has revealed that most papers had only considered individual farm operations, while the pork supply chain management involves the coordination of sets of farm units at different stages of production. Thus, our contribution emphasizes the importance and complexity of new decision-making tasks regarding the modern organization of the pork sector. All these elements make it possible to envisage new opportunities for operations research methods to be successfully applied to the pork supply chain. Likewise, we have identified some existing gaps in the literature that we believe should be addressed in the near future.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Allen, M. A., & Stewart, T. S. (1983). A simulation model for a swine breeding unit producing feeder pigs. Agricultural Systems, 10, 193–211.

    Article  Google Scholar 

  • Ahumada, O., & Villalobos, J. R. (2009). Application of planning models in the agri-food supply chain: a review. European Journal of Operational Research, 196(1), 1–20.

    Article  Google Scholar 

  • Backus, G., & Dijkhuizen, A. A. (2002). Kernkamp lecture: the future of the European pork chain. In Allen D. Leman swine conference, Minnesota, USA (pp. 8–11).

    Google Scholar 

  • Bailleul, P. J. D., Bernier, J. F., van Milgen, J., Sauvant, D., & Pomar, C. (2000). The utilization of prediction models to optimize farm animal production systems: the case of a growing pig model. In J. P. McNamara, J. France, & D. Beever (Eds.), Modelling nutrient utilization in farm animals (pp. 379–392). Wallingford: CABI Publishing.

    Chapter  Google Scholar 

  • Balogh, P., Ertsey, I., Fenyves, V., & Nagy, L. (2009). Analysis and optimization regarding the activity of a Hungarian pig sales and purchased cooperation. Studies in Agricultural Economics, 109, 35–54.

    Google Scholar 

  • Bloemhof, J. M., Smeets, C. M., & van Nunen, J. A. E. E. (2004). Supply chain optimization in animal husbandry. Erasmus Research Institute of Management. In B. Fleischmann & A. Klose (Eds.), Lecture notes in econometrics and mathematical systems: Vol. 544. Distribution logistics; advanced solutions to practical problems (pp. 47–64). Berlin: Springer.

    Google Scholar 

  • Boland, M. A., Preckel, P. V., & Schinckel, A. P. (1993). Optimal hog slaughter weights under alternative pricing systems. Journal of Agriculture and Applied Economics, 25(2), 148–163.

    Google Scholar 

  • Boys, K. A., Li, N., Preckel, P. V., Schinckel, A. P., & Foster, K. A. (2007). Economic replacement of a heterogeneous herd. American Journal of Agricultural Economics, 89, 24–35.

    Article  Google Scholar 

  • Broek, J. V. D., Schütz, P., Stougie, L., & Tomasgard, A. (2006). Location of slaughterhouses under economies of scale. European Journal of Operational Research, 175(2), 740–750.

    Article  Google Scholar 

  • Broekmans, J. E. (1992). Influence of price fluctuations on delivery strategies for slaughter pigs. Dina Nota, 7, 1–24.

    Google Scholar 

  • Bookbinder, J. H., & Matuk, T. A. (2009). Logistics and Transportation in Global Supply Chains: Review, Critique, and Prospects. In Tutorials in Operations Research INFORMS (pp. 182–211). ISBN 978-1-877640-24-7.

    Google Scholar 

  • Cachon, G. (2003). Supply chain coordination with contracts. In S.G. deKok (Ed.), Handbooks in operations Research and Management Science: Supply Chain Management, Amsterdam: North-Holland. Chap. 11.

    Google Scholar 

  • Chavas, J. P., Kliebenstein, J., & Crenshaw, J. D. (1985). Modeling dynamical agricultural production response: the case of swine production. American Journal of Agricultural Economics, 67(3), 636–646.

    Article  Google Scholar 

  • Christopher, M. (1998). Logistics and supply chain management. strategies for reducing cost and improving service. London: Prentice Hall.

    Google Scholar 

  • Chopra, S., & Meindl, P. (2007). Supply chain management: strategic, planning and operation. Upper Saddle River: Prentice-Hall.

    Google Scholar 

  • Christou, I. T. (2012). Quantitative methods in supply chain management. models and algorithms. London: Springer.

    Book  Google Scholar 

  • Dijkhuizen, A. A., Morris, R. S., & Morrow, M. (1986). Economic optimization of culling strategies in swine breeding herds, using the “PORKCHOP computer program”. Preventive Veterinary Medicine, 4, 341–353.

    Article  Google Scholar 

  • Faostat (2012). Statistics of livestock primary in the section of Production. Downloadable from the webpage http://faostat.fao.org/site/573/default.aspx#ancor. Last access February 23th, 2012.

  • Filho, K. E. (2004). Supply chain approach to sustainable beef production from a Brazilian perspective. Livestock Production Science, 90, 53–61.

    Article  Google Scholar 

  • Gribkovskaia, I., Gullberg, B. O., Hovden, K., & Wallance, S. W. (2006). Optimization model for a livestock collection problem. International Journal of Physical Distribution & Logistics Management, 36(2), 136–152.

    Article  Google Scholar 

  • Higgins, A. J., & Laredo, L. A. (2006). Improving harvesting and transport planning within a sugar value chain. Journal of the Operational Research Society, 57(4), 367–376.

    Article  Google Scholar 

  • Higgins, A. J., Miller, C. J., Archer, A. A., Ton, T., Fletcher, C. S., & McAllister, R. R. J. (2009). Challenges of operations research practice in agricultural value chains. Journal of the Operational Research Society, 61, 964–973.

    Article  Google Scholar 

  • Hobbs, J. E., Kerr, W. A., & Klein, K. K. (1998). Creating international competitiveness through supply chain management: Danish pork. Supply Chain Management: An International Journal, 3(2), 68–78.

    Article  Google Scholar 

  • Hobbs, J. E., & Young, L. M. (2000). Closer vertical co-ordination in agri-food supply chains: a conceptual framework and some preliminary evidence. Supply chain Management: An International Journal, 5(3), 131–143.

    Article  Google Scholar 

  • Huirne, R. B., Dijkhuizen, A. A., Van Beek, P., & Hendriks, Th. H. B. (1993). Stochastic dynamic programming to support sow replacement decisions. European Journal of Operational Research, 67, 161–171.

    Article  Google Scholar 

  • Jalving, A. W., Dijkhuizen, A. A., & van Arendonk, J. A. M. (1992). Dynamic probabilistic modelling of reproduction and management in sow herds. General aspects and model description. Agricultural Systems, 39, 133–152.

    Article  Google Scholar 

  • Jørgensen, E. (1993). The influence of weighing precision on delivery decision in slaughter pig production. Acta Agriculture Scandinavica, Section A, Animal Science, 43, 181–189.

    Article  Google Scholar 

  • Khamjan, S., Piewthongngam, K., & Pathumnakul, S. (2013). Pig procurement plan considering pig growth and size distribution. Computers & Industrial Engineering, 64(4), 886–894.

    Article  Google Scholar 

  • Kamp, J. A. L. M. (1999). Knowledge based systems: from research to practical application: pitfalls and critical success factors. Computers & Electronics in Agriculture, 22(2–3), 243–250.

    Article  Google Scholar 

  • Kohls, R. L., & Uhl, J. N. (2002). Marketing of agricultural products (9th ed.). Upper Saddle River: Prentice Hall.

    Google Scholar 

  • Krieter, J. (2002). Evaluation of different pig production systems including economic, welfare and environmental aspects. Archiv für Tierzucht, 45(3), 223–235.

    Google Scholar 

  • Kristensen, A. R., Jørgensen, E., & Toft, N. (2012). Herd Management Science. II. Advanced topics http://www.prodstyr.ihh.kvl.dk/vp/2011/book.htm. Academic Books ISBN: 9788763461214.

  • Kristensen, A. R., & Søllested, T. A. (2004a). A sow replacement model using Bayesian updating in a three-level hierarchic Markov process I. Biological model. Livestock Production Sciences, 87, 13–24.

    Article  Google Scholar 

  • Kristensen, A. R., & Søllested, T. A. (2004b). A sow replacement model using Bayesian updating in a three-level hierarchic Markov process II. Optimization model. Livestock Production Sciences, 87, 25–36.

    Article  Google Scholar 

  • Kristensen, A. R., Nielsen, L., & Hielsen, M. S. (2012). Optimal slaughter pig marketing with emphasis on information from on-line live weight assessment. Livestock Science, 145, 95–108.

    Article  Google Scholar 

  • Kure, H. (1997). Marketing Management support in slaughter pig production. Ph.D. dissertation, Department of Animal Science and Animal Health, The Royal Veterinary and Agricultural University, Copenhagen.

  • Liang, J., Fabiosa, J. F., Jensen, H. H., & Miller, G. Y. (2010). Potential HPAI shocks and welfare implications of market power in the US broiler industry. Agricultural and Applied Economics Association. Joint Annual Meeting, Denver, Colorado.

  • Manzini, R., & Gebennini, E. (2008). Optimization models for the dynamic facility location and allocation problem. International Journal of Production Research, 46(8), 2061–2086.

    Article  Google Scholar 

  • Marsh, W. E. (1986). Economic decision making on health and management livestock herds: examining complex problems through computer simulation. Ph.D. Dissertation, University of Minnesota, St. Paul.

  • Martel, G., Dedieu, B., & Dourmad, J. Y. (2008). Simulation of sow herd dynamics with emphasis on performance and distribution of periodic task events. Journal of Agricultural Science, 146, 365–380.

    Google Scholar 

  • Martinez, S. W., & Reed, A. (1996). From farmers to consumers. Vertical coordination in the food Industry. Economic Research Service. Report, No. 720, USDA, Washington.

  • McCown, R. L. (2002). Locating agricultural decision support systems in the troubled past and sociotechnical compexity of ‘models for management’. Agricultural Systems, 74(1), 11–25.

    Article  Google Scholar 

  • Melo, M. T., Nickel, S., & Saldanha-da-Gama, F. (2009). Facility location and supply chain management—a review. European Journal of Operational Research, 119, 14–34.

    Google Scholar 

  • Min, H., & Zhou, G. (2002). Supply chain modelling: past, present and future. Computers & Industrial Engineering, 43, 231–249.

    Article  Google Scholar 

  • Nadal, E., & Plà, L. M. (2013). Optimal planning of pig transfers along a pig supply chain by a mixed integer linear programming model. Submitted to the Journal of the Operational Research Society.

  • Niemi, J. K. (2006). A dynamic programming model for optimizing feeding and slaughter decisions regarding fattening pigs. Agricultural and Food Science, 15, 6–121.

    Google Scholar 

  • Ohlmann, J. W., & Jones, P. C. (2011). An integer programming model for optimal pork marketing. Annals of Operations Research, 190(1), 271–287.

    Article  Google Scholar 

  • Oppen, J., & Løkketangen, A. (2008). A tabu search approach for the livestock collection problem. Computers & Operations Research, 35(10), 3213–3229.

    Article  Google Scholar 

  • Oppen, J., Løkketangen, A., & Desrosiers, J. (2010). Solving a rich vehicle routing and inventory using column generation. Computers & Operations Research, 37(7), 1308–1317.

    Article  Google Scholar 

  • Ouden, M., Dijkhuizen, A. A., Huirne, R. B. M., & Zuurbier, P. J. P. (1996). Vertical cooperation in agricultural production marketing chains, with special reference to product differentiation in pork. Agribusiness, 12, 277–290.

    Article  Google Scholar 

  • Ouden, M., Huirne, R. B. M., Dijkhuizen, A. A., & van Beek, P. (1997a). Economic optimization of pork production-marketing chains: II. Modelling outcome. Livestock Production Science, 48, 39–50.

    Article  Google Scholar 

  • Ouden, M., Nijsing, J. T., Dijkhuizen, A. A., & Huirne, R. B. M. (1997b). Economic optimization of pork production-marketing chains: I. Model input on animal welfare and cost. Livestock Production Science, 48, 23–37.

    Article  Google Scholar 

  • Perez, C., de Castro, R., & Font i Furnols, M. (2009). The pork industry: a supply chain perspective. British Food Journal, 111(3), 257–274.

    Article  Google Scholar 

  • Perez, C., de Castro, R., Simons, D., & Gimenez, G. (2010). Development of lean supply chains: A case study of the Catalan pork sector. Supply Chain Management, 11:271–280.

    Google Scholar 

  • Pettigrew, J. E., Cornelius, S. G., Eidman, V. R., & Moser, R. L. (1986). Integration of factors affecting sow efficiency: a modelling approach. Journal of Animal Science, 63, 1314–1321.

    Google Scholar 

  • Plà-Aragonés, L. M., Rodríguez-Sánchez, S. V., & Rebillas-Loredo, V. (2013, accepted). A mixed integer linear programming model for optimal delivery of fattened pigs to the abattoir. Journal of Applied Operations Research.

  • Plà, L. M. (2006). Tactical supply chain model of pig production. Proceedings of the Second Meeting of the EURO Working group on Operational Research (OR) in Agriculture and Forest Management. Journal of Agricultural Science, 144(5), 467–472.

    Article  Google Scholar 

  • Plà, L. M. (2007). Review of mathematical models for sow herd management. Livestock Science, 106, 107–119.

    Article  Google Scholar 

  • Plà, L. M., Conde, J., & Pomar, J. (1998). Sow model for decision aid at farm level. In F. J. Giron (Ed.), Applied decision analysis, Boston: Kluwer Academic.

    Google Scholar 

  • Plà, L. M., Pomar, C., & Pomar, J. (2003). A Markov decision sow model representing the productive lifespan of sows. Agricultural Systems, 76, 253–272.

    Article  Google Scholar 

  • Plà, L. M., Faulin, J., & Rodriguez, S. V. (2009). A linear programming formulation of a semi-Markov model to design pig facilities. Journal of the Operational Research Society, 60(5), 619–625.

    Article  Google Scholar 

  • Plà, L. M., Sandars, D., & Higgins, A. (2013, accepted). A perspective on Operational Research prospects for agriculture. Journal of Operational Research Society. doi:10.1057/jors.2913.45

  • Pibernik, R., & Sucky, E. (2007). An approach to inter-domain master planning in supply chains. International Journal of Production Economics, 108, 200–212.

    Article  Google Scholar 

  • Pomar, C., Harris, D. L., & Minvielle, F. (1991). Computer simulation model of swine production systems: III. A dynamic herd simulation model including production. Journal of Animal Science, 69, 2822–2836.

    Google Scholar 

  • Rodriguez, S. V., Albornoz, V., & Plà, L. M. (2009). A two stage stochastic programming model for scheduling replacements in sow farms. TOP, 17(1), 171–179.

    Article  Google Scholar 

  • Rodriguez, S. V. (2010). Models under uncertainty to support sow herd management in the context of the Pork Supply Chain Supply. Ph.D. Dissertation, Department of Mathematics. University of Lleida, Spain.

  • Rodriguez, S. V., Jensen, T., Plà, L. M., & Kristensen, A. (2011). Optimal replacement policies and economic value of clinical observations in sow herd. Livestock Science, 138, 207–219.

    Article  Google Scholar 

  • Roo, G. (1987). A stochastic model to study breeding schemes in a small pig population. Agricultural Systems, 25, 1–25.

    Article  Google Scholar 

  • Singh, D. (1986). Simulation of swine herd population dynamics. Agricultural Systems, 22, 157–183.

    Article  Google Scholar 

  • Stadler, H. (2005). Supply chain management and advanced planning-basics, overview and challenges. European Journal of Operational Research, 163, 575–588.

    Article  Google Scholar 

  • Schütz, P., Stougie, L., & Tomasgard, A. (2008). Stochastic facility location with general long-run costs and convex short-run costs. Computers & Operations Research, 35(9), 2988–3000.

    Article  Google Scholar 

  • Schütz, P., Tomasgard, A., & Ahmed, S. (2009). Supply chain design under uncertainty using sample average approximation and dual decomposition. European Journal of Operational Research, 199(2), 409–419.

    Article  Google Scholar 

  • Taylor, D. H. (2006). Strategic consideration in the development of lean agri-food supply chains: a case study of the UK pork sector. Supply Chain Management: An International Journal, 11(3), 271–280.

    Article  Google Scholar 

  • Tess, M. W., Bennett, G. L., & Dickerson, G. E. (1983). Simulation of genetic changes in life cycle efficiency of pork production. I. A bioeconomic model. Journal of Animal Science, 56, 336–353.

    Google Scholar 

  • Toft, N. (1998). The dynamic aspect of the reproductive performance in the sow herd. Dina Notat No. 70.

  • Trienekens, J., Petersen, B., Wognum, N., & Brinkmann, D. (2009). European pork chains. In Diversity and quality challenges in consumer-oriented production and distribution, Wageningen Academic: Wageningen. ISBN 978-90-8686-103-3.

    Google Scholar 

  • Upton, M. (1989). Livestock productivity assessment and herd growth models. Agricultural Systems, 29, 149–164.

    Article  Google Scholar 

  • van der Gaag, M., Vos, F., Saatkamp, H. W., van Boven, M., van Beek, P., & Huirne, R. B. M. (2004). A state-transition simulation model for the spread of salmonella in the pork supply chain. European Journal of Operational Research, 156, 782–798.

    Article  Google Scholar 

  • van der Vorst, J. G. A. J., da Silva C. A, & Trienekens, J. H. (2007). Agro-industrial supply chain Management: Concepts and applications. Food and Agriculture Organization of the United Nations, Rome. Agricultural Management, Marketing and Finance, 17.

  • Whittemore, C. T., & Kyriazakis, I. (2006). Whittemore’s science and practice of pig production. London: Blackwell.

    Google Scholar 

Download references

Acknowledgements

The authors appreciate the financial help from the Working Community of the Pyrenees in the development of this research (code IIQ13172.RI1-CTP09-R2). Sara V. Rodriguez acknowledges the Mexican Mathematical Society-Sofia Kovalevskaia Foundation, the project NPTC founded by PROMEP PROMEAP/103.5/11/4330, and the AMC-FUMEC for the grant received during the development of this work. Lluis M. Plà wishes to acknowledge the financial support of the Spanish Research Program (MTM2005-09362-C03-02, AGL2009-12026 and MTM2009-14087-C04-01). Javier Faulin wants also to recognize the financial aid of the Spanish Ministry of Science with the project TRA2010-21644-C03-01 and the support of the Research Network “Sustainable TransMET” funded by the Government of Navarre (Spain) in the Program “Jerónimo de Ayanz”.

Author information

Authors and Affiliations

  1. Graduate Program in System Engineering 111-F, Universidad Autonoma de Nuevo Leon, Ciudad Universitaria San Nicolas de los Garza, NL, 66450, Mexico

    Sara V. Rodríguez

  2. Department of Mathematics, University of Lleida, Jaume II, 73, 25001, Lleida, Spain

    Sara V. Rodríguez & Lluis M. Plà

  3. Department of Statistics and Operations Research, Public University of Navarre, Los Magnolios Blg, 1st floor, 31006, Pamplona, Spain

    Javier Faulin

Authors
  1. Sara V. Rodríguez
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lluis M. Plà
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Javier Faulin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lluis M. Plà.

Appendix

Appendix

Table 1 List of models for Pork Supply Chain Management
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rodríguez, S.V., Plà, L.M. & Faulin, J. New opportunities in operations research to improve pork supply chain efficiency. Ann Oper Res 219, 5–23 (2014). https://doi.org/10.1007/s10479-013-1465-6

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-013-1465-6

Keywords

Search

Navigation