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Integration of strategic and operational attributes to calculate the optimal cultivation of crops
194 viewed

Integration of strategic and operational attributes to calculate the optimal cultivation of crops

Mehrpour, M. R

Integration of strategic and operational attributes to calculate the optimal cultivation of crops

Mehrpour, M. R ; Sharif University of Technology | 2024

194 Viewed
  1. Type of Document: Article
  2. DOI: 10.1016/j.eswa.2023.121238
  3. Publisher: Elsevier , 2024
  4. Abstract:
  5. Determining the optimal quantity of crops is crucial for establishing a sustainable cultivation pattern when multiple potential crops are available. To address this issue, we propose a novel hybrid multi-attribute optimization model (MAOM) based on two steps. Firstly, we calculate the sustainability score of candidate crops by taking into account strategic criteria categorized in terms of sustainability, including economic, social, and environmental dimensions. To ensure a more reliable choice, we develop a risk-averse UTA (UTilité Additive) to adjust the trade-off among the criteria of alternatives in multi-criteria decision-making (MCDM) problems. Secondly, we develop a linear optimization model to calculate the optimal amount of candidate crops based on the sustainability score and operational criteria. We employ this framework to determine the optimal cultivation pattern in Khorasan Razavi, Iran. The results suggest that Dried Garlic, Turnip, Forage, Millet, and Khasil are suitable crops for the six-month period of spring and summer, while Potato, Fodder Beet, Shah Seed, and Mung Bean are the optimal alternatives for the six-month period of autumn and winter among the 46 candidate crops. Finally, a conclusion is drawn and recommendations for further research are proposed. © 2023 The Author(s)
  6. Keywords:
  7. Linear optimization model ; Multi-attribute optimization model (MAOM) ; Optimal cultivation ; Risk-averse UTA (UTilité Additive) ; Sustainability ; Crops ; Decision making ; Economic and social effects
  8. Source: Expert Systems with Applications ; Volume 236 , 2024 ; 09574174 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S0957417423017402