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A hybrid probabilistic fuzzy goal programming approach for agricultural decision-making

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  • Jana, R.K.
  • Sharma, Dinesh K.
  • Chakraborty, B.

Abstract

In this paper, we present a probabilistic fuzzy goal programming model to capture different uncertainties in an agricultural decision-making environment. First, we construct the goals of the model as probabilistic fuzzy goals. Next, we convert the probabilistic fuzzy goal programming problem to a probabilistic constrained programming problem. While a deterministic solution to this problem cannot be derived, we use a hybrid approach comprising Monte-Carlo simulation and a real-coded genetic algorithm. The application of the proposed model and the solution technique is demonstrated by considering the agricultural planning of the Danton-II community development block of Paschim Medinipur District, West Bengal, India.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:173:y:2016:i:c:p:134-141
    DOI: 10.1016/j.ijpe.2015.12.010
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    References listed on IDEAS

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    1. 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.
    2. Sinha, S. B. & Rao, K. A. & Mangaraj, B. K., 1988. "Fuzzy goal programming in multi-criteria decision systems: A case study in agricultural planning," Socio-Economic Planning Sciences, Elsevier, vol. 22(2), pages 93-101.
    3. Paudyal, G. N. & Das Gupta, A., 1990. "A nonlinear chance constrained model for irrigation planning," Agricultural Water Management, Elsevier, vol. 18(2), pages 87-100, July.
    4. Richard L. Simmons & Carlos Pomareda, 1975. "Equilibrium Quantity and Timing of Mexican Vegetable Exports," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 57(3), pages 472-479.
    5. Zeng, Xieting & Kang, Shaozhong & Li, Fusheng & Zhang, Lu & Guo, Ping, 2010. "Fuzzy multi-objective linear programming applying to crop area planning," Agricultural Water Management, Elsevier, vol. 98(1), pages 134-142, December.
    6. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
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    Cited by:

    1. Dong Hee Suh & Charles B. Moss, 2021. "Examining the Input and Output Linkages in Agricultural Production Systems," Agriculture, MDPI, vol. 11(1), pages 1-13, January.
    2. Rabin K. Jana & Dinesh K. Sharma & Peeyush Mehta, 2022. "A probabilistic fuzzy goal programming model for managing the supply of emergency relief materials," Annals of Operations Research, Springer, vol. 319(1), pages 149-172, December.
    3. Dinçer, Hasan & Yüksel, Serhat, 2019. "An integrated stochastic fuzzy MCDM approach to the balanced scorecard-based service evaluation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 166(C), pages 93-112.

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