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Fuzzy goal programming based genetic algorithm approach to nutrient management for rice crop planning

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  • Sharma, Dinesh K.
  • Jana, R.K.

Abstract

The main purpose of this paper is to present a tolerance based fuzzy goal programming (FGP) and a FGP based genetic algorithm (GA) model for nutrient management decision-making for rice crop planning in India. In the proposed model, we have included fuzzy goals such as fertilizer cost and rice yield in the decision-making process. Fuzzy goals are converted to goal constraints using their corresponding membership function values and the deterministic equivalent of the fuzzy model is obtained using tolerance based FGP approach. This deterministic nutrient management model is also solved using a proposed real coded GA and the optimal combination of fertilizer is obtained to maximize the yield of rice within the available budget. A case example is solved under various scenarios to demonstrate the proposed approach.

Suggested Citation

  • Sharma, Dinesh K. & Jana, R.K., 2009. "Fuzzy goal programming based genetic algorithm approach to nutrient management for rice crop planning," International Journal of Production Economics, Elsevier, vol. 121(1), pages 224-232, September.
    • Handle: RePEc:eee:proeco:v:121:y:2009:i:1:p:224-232
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    Cited by:

    1. Abbas Amini Fasakhodi & Seyed Nouri & Manouchehr Amini, 2010. "Water Resources Sustainability and Optimal Cropping Pattern in Farming Systems; A Multi-Objective Fractional Goal Programming Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4639-4657, December.
    2. Zgajnar, Jaka & Kavcic, Stane, 2012. "Farm management support based on mathematical programming; an example of fertilization planning," Agroeconomia Croatica, Croatian Society of Agricultural Economists, vol. 2(1), pages 1-8, March.
    3. Jana, R.K. & Sharma, Dinesh K. & Chakraborty, B., 2016. "A hybrid probabilistic fuzzy goal programming approach for agricultural decision-making," International Journal of Production Economics, Elsevier, vol. 173(C), pages 134-141.
    4. Danilo Liuzzi & Veronica Lupi & Aymeric Vié, 2022. "Sustainability, cooperation and mobility of workers within and between European countries: a two-stage goal programming model," Annals of Operations Research, Springer, vol. 311(2), pages 749-769, April.
    5. Ramtin Joolaie & Ahmad Abedi Sarvestani & Fatemeh Taheri & Steven Van Passel & Hossein Azadi, 2017. "Sustainable cropping pattern in North Iran: application of fuzzy goal programming," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(6), pages 2199-2216, December.
    6. Lokesh Jain & Harish Kumar & R. K. Singla, 2015. "Assessing Mobile Technology Usage for Knowledge Dissemination among Farmers in Punjab," Information Technology for Development, Taylor & Francis Journals, vol. 21(4), pages 668-676, October.
    7. Liu, Qingyu & Shen, Bin & Wen, Xin, 2023. "Role of climate-smart agriculture in fighting against climate change in competitive supply chains," International Journal of Production Economics, Elsevier, vol. 264(C).
    8. Borodin, Valeria & Bourtembourg, Jean & Hnaien, Faicel & Labadie, Nacima, 2016. "Handling uncertainty in agricultural supply chain management: A state of the art," European Journal of Operational Research, Elsevier, vol. 254(2), pages 348-359.

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