Abdeshahi, A., Mardani Najafabadi, M., Zeinali, M. (2020). Determining the Optimal Cropping Pattern of Agricultural Crops in Mollasani Coumty of Iran: Application of Robust Multi-Objective Optimization Model. , 28(3), 175-203. doi: 10.30490/aead.2020.304989.1090
Abbas Abdeshahi; M. Mardani Najafabadi; Monireh Zeinali. "Determining the Optimal Cropping Pattern of Agricultural Crops in Mollasani Coumty of Iran: Application of Robust Multi-Objective Optimization Model". , 28, 3, 2020, 175-203. doi: 10.30490/aead.2020.304989.1090
Abdeshahi, A., Mardani Najafabadi, M., Zeinali, M. (2020). 'Determining the Optimal Cropping Pattern of Agricultural Crops in Mollasani Coumty of Iran: Application of Robust Multi-Objective Optimization Model', , 28(3), pp. 175-203. doi: 10.30490/aead.2020.304989.1090
Abdeshahi, A., Mardani Najafabadi, M., Zeinali, M. Determining the Optimal Cropping Pattern of Agricultural Crops in Mollasani Coumty of Iran: Application of Robust Multi-Objective Optimization Model. , 2020; 28(3): 175-203. doi: 10.30490/aead.2020.304989.1090

Determining the Optimal Cropping Pattern of Agricultural Crops in Mollasani Coumty of Iran: Application of Robust Multi-Objective Optimization Model

اقتصاد کشاورزی و توسعه
Volume 28, Issue 3 - Serial Number 111, December 2020, Pages 175-203    PDF (438.7 K)
Document Type: Original Article
DOI: 10.30490/aead.2020.304989.1090
Authors
Abbas Abdeshahi* 1; M. Mardani Najafabadi2; Monireh Zeinali3
1Associate Professor of Agricultural Economics, Department of Agricultural Economics, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Ahvaz, Iran
2Assistant Professor of Agricultural Economics, Department of Agricultural Economics, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Ahvaz, Iran
3MSc Graduate in Agricultural Economics, University of Zabol, Zabol, Iran
Abstract
In this study to determine optimum crop pattern of the county of Molasani, linear multi-objective planning model include economic, social and environmental objectives has been used in two phases. In the first phase of the study, the uncertainty in the data is ignored, but in the second phase, the mentioned feature is included and the results of each of them are discussed separately. Necessary data were collected from government agencies for the 2014-15 crop year and the models were coded in GAMS software. According to the results in the first phase, barely acreage increased from 4 to 5.74 thousand hectares (43.55 percent) and vegetables acreage increased from 300 to 410 hectares (37.38 percent). Also, in this phase rapeseed acreage decreased from 500 to 120 hectares (75.34 percent) and wheat acreage decreased by 12.43 percent. In the second phase of the study, it was found that there is a mutual relationship between the benefits of the optimal cropping pattern and the level of protection against uncertain data; such that by increasing the level of deviation from constraint from 10% to 50%, the gross profit decreases by 2.5%. The results can help agricultural decision makers achieve the goal of maximizing profit, averaging 5% more than the current cropping pattern, by considering several different goals and avoiding wastage of scarce and valuable resources.
Keywords
Multi-Objective Programming; Uncertainty; Cropping Pattern; Molasani
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