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Nearly optimal linear programming as a guide to agricultural planning

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  • Scott R. Jeffrey
  • Ron R. Gibson
  • Merle D. Faminow

Abstract

Linear programming has long been used as a tool in agricultural planning. This paper presents and discusses a technique that can be used in conjunction with linear programming to evaluate ‘nearly optimal’ solutions. This technique is referred to as Nearly Optimal Linear Programming or Modelling to Generate Alternatives (MGA). MGA allows planners to incorporate important objectives that are difficult to include in a mathematical model by identifying and evaluating alternative ‘nearly optimal’ solutions. Some of these alternative solutions may be consistent with the goals or objectives of decision makers. To date, MGA has received little use in addressing agricultural planning problems. A micro‐level application of MGA, concerning a dairy ration formulation problem, is presented to demonstrate the relevance of MGA to agricultural planning by decision makers. Within this application, the use of MGA to complement and enhance normal linear programming analysis is also discussed.

Suggested Citation

  • Scott R. Jeffrey & Ron R. Gibson & Merle D. Faminow, 1992. "Nearly optimal linear programming as a guide to agricultural planning," Agricultural Economics, International Association of Agricultural Economists, vol. 8(1), pages 1-19, December.
    • Handle: RePEc:bla:agecon:v:8:y:1992:i:1:p:1-19
    DOI: 10.1111/j.1574-0862.1992.tb00227.x
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    Cited by:

    1. Abdulkadri, Abdullahi O. & Ajibefun, Igbekele A., 1998. "Developing alternative farm plans for cropping system decision making," Agricultural Systems, Elsevier, vol. 56(4), pages 431-442, April.
    2. Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, vol. 94(3), pages 622-636, June.
    3. Makowski, David & Hendrix, Eligius M. T. & van Ittersum, Martin K. & Rossing, Walter A. H., 2001. "Generation and presentation of nearly optimal solutions for mixed-integer linear programming, applied to a case in farming system design," European Journal of Operational Research, Elsevier, vol. 132(2), pages 425-438, July.
    4. Janssen, Sander J.C. & van Ittersum, Martin K., 2007. "Assessing farmer behaviour as affected by policy and technological innovations: bio-economic farm models," Reports 9293, Wageningen University, SEAMLESS: System for Environmental and Agricultural Modelling; Linking European Science and Society.
    5. Jorge Andres Garcia & Angelos Alamanos, 2022. "Integrated Modelling Approaches for Sustainable Agri-Economic Growth and Environmental Improvement: Examples from Greece, Canada and Ireland," Land, MDPI, vol. 11(9), pages 1-19, September.

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