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Crop planning optimization model: the validation and verification processes

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Abstract

Each optimization problem in the area of natural resources claims for a specific validation and verification (V&V) procedures which, for overwhelming majority of the models, have not been developed so far. In this paper we develop V&V procedures for the crop planning optimization models in agriculture when the randomness of harvests is considered and complex crop rotation restrictions must hold. We list the criteria for developing V&V processes in this particular case, discuss the restrictions given by the data availability and suggest the V&V procedures. To show its relevance, they are applied to recently constructed stochastic programming model aiming to serve as a decision support tool for crop plan optimization in South Moravian farm. We find that the model is verified and valid and if applied in practice—it thus offers a plausible alternative to standard decision making routine on farms which often leads to breaking the crop rotation rules.

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References

  • Bachinger J, Zander P (2007) ROTOR, a tool for generating and evaluating crop rotations for organic farming systems. Eur J Agron 26: 130–143

    Article  Google Scholar 

  • Benjamin LR, Milne AE, Parsons DJ, Cussans J, Lutman PJW (2009) Using stochastic dynamic programming to support weed management decisions over a rotation. Weed Res 49(2): 207–216

    Article  Google Scholar 

  • Bohle C, Maturana S, Vera JA (2009) A robust optimization approach to wine grape harvesting scheduling, Eur J Oper Res. doi:10.1016/j.ejor.2008.12.003

  • Bravo M, Gonzales I (2008) Applying stochastic goal programming: a case study on water use planning. Eur J Oper Res. doi:10.1016/j.ejor.2008.04.034

  • Castellazzi MS et al (2008) A systematic representation of crop rotations. Agr Syst 97: 26–33

    Article  Google Scholar 

  • Crohn DM (2006) Optimizing organic fertilizer applications under steady-state conditions. J Environ Qual 35(2): 658–669

    Article  Google Scholar 

  • Detlefsen NK, Jensen AL (2007) optimal crop sequences using network flows. Agr Syst 94(2): 566–572

    Article  Google Scholar 

  • Dogliotti S, Rossing WAH, van Ittersum MK (2003) ROTAT, a tool for systematically generating crop rotations. EUR J Agron 19(2): 239–250

    Article  Google Scholar 

  • Elton EJ, Gruber MJ (1997) Modern portfolio theory, 1950 to date. J Bank Finan 21: 1743–1759

    Article  Google Scholar 

  • Freund RJ (1956) The introduction of risk into a programming model. Econometrica 24: 253–263

    Article  Google Scholar 

  • Georgiou PE, Papamichail DM (2008) Optimization model of an irrigation reservoir for water allocation and crop planning under various weather conditions. Irrigation Sci 26(6): 487–504

    Article  Google Scholar 

  • Gudbrand L et al (2009) Risk programming and sparce data: how to get more reliable results. Agric Syst 101: 42–48

    Article  Google Scholar 

  • Halachmi I et al (2001) Validation of simulation model for robotic milkin barn design. Eur J Oper Res 134: 677–688

    Article  Google Scholar 

  • Hanveled WKK, Stegeman AW (2005) Crop succession requirements in agricultural production planning. Eur J Oper Res 166: 406–429

    Article  Google Scholar 

  • Hardaker JB, Huirne RBM, Anderson JR (2004) Coping with Risk in Agriculture. CAB International, Wallingford

    Book  Google Scholar 

  • Hasuike T, Ishii H (2009) Probability maximization models for portfolio selection under ambiguity. CEJOR 17(2): 159–180

    Article  Google Scholar 

  • Janova J (2010) Optimization models in agriculture and natural resources: the validation and verification process. In: 28th international conference on mathematical methods in economics 2010, 08–10 Sep 2010 Ceske Budejovice, Czech Republic, pp 315–320

  • Janová J, Ambrožová P (2009) Optimization of production planning in Czech agriculture co-operative via linear programming. Acta univ agric et silvic Mendel Brun 57(6): 99–104

    Google Scholar 

  • Jatoe JBD, Yiridoe EK, Weersink A, Clark JS (2008) Economic and environmental impacts of introducing land use policies and rotations on Prince Edward Island potato farms. Land Use Policy 25(3): 309–319

    Article  Google Scholar 

  • Kraus A, Litzenberger R (1976) Skewness preference and the valuation of risky assets. J Finan 21(4): 1085–1100

    Google Scholar 

  • Kurlavicius A (2008) Optimization of the agricultural production structure. In: Proceedings of 20th international conference, EURO mini conference Continuos optimization and knowledge based technologies, pp 370–375

  • Lee CF (1977) Functional form, skewness effect, and risk-return relationship. J Finan Quant Anal 12(1): 55–72

    Article  Google Scholar 

  • Maatman A, Schweigman C, Ruijs A, van der Vlerk MH (2002) Modeling farmer’s response to uncertain rain fall in Burkina Faso: a stochastic programming approach. Oper Res 50: 399–414

    Article  Google Scholar 

  • Markowitz H (1952) Portfolio selection. J Finan 7: 77–91

    Google Scholar 

  • Musshoff O, Hirschauer N (2007) Improved program planning with formal models? The case of high risk crop farming in Northeast Germany. CEJOR 15: 127–141

    Article  Google Scholar 

  • Pap Z (2008) Crop rotation constraints in agricultural production planning. In: Proceedings of 6th international symposium on intelligent systems and informatics, pp 247–251

  • Parsons DJ, Benjamin LR, Clarke J, Ginsburg D, Mayes A, Milne AE, Wilkinson DJ (2009) Weed manager-a model-based decision support system for weed management in arable crops. Comput Electron Agric 65(2): 155–167

    Article  Google Scholar 

  • Rubinstein M (2002) Markowitz’s “portfolio selection”: a fifty-year retrospective. J Finan 57: 1041–1045

    Article  Google Scholar 

  • Seppelt R (2000) Regionalised optimum control problems for agroecosystem management. Ecol Model 131(2-3): 121–132

    Article  Google Scholar 

  • Torkamani J (2005) Using whole-farm modeling approach to assess prospective technologies under uncertainity. Agric Syst 85: 138–154

    Article  Google Scholar 

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Correspondence to Jitka Janová.

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Janová, J. Crop planning optimization model: the validation and verification processes. Cent Eur J Oper Res 20, 451–462 (2012). https://doi.org/10.1007/s10100-011-0205-8

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