Determining the Optimal Cropping Pattern with Emphasis on Proper Use of Sustainable Agricultural Disruptive Inputs: Application of Robust Multi-Objective Linear Fractional Programming

Document Type : Research Paper

Authors

Abstract

      One of the challenges in developing of sustainable agriculture is the non-optimal and excessive use of disruptive inputs of sustainable agriculture. The purpose of this study was to optimize the cropping pattern in the lands of drainage and Irrigation network of Mianab-e- Shooshtar with an emphasis on reducing the use of chemical fertilizers and pesticides. For this purpose, the multi-objective fractional linear programming method was used without and with considering uncertainty (scenarios 1 and 2, respectively) via robust optimization. Data were collected from Agricultural Jihad Organization, Water and Power Organization of Khuzestan and the Utilization Company of Karun Irrigation Networks in 2017-2018 cropping year. The results showed that in the second scenario, the amount of fertilizer, pesticides, crop area and irrigation water consumption decreased by 17, 15, 8 and 1.1 percent, respectively. It was also found that increasing the system's protection against uncertainty, decreases the use of fertilizers and chemical pesticides. Therefore, the optimal cultivation pattern of robust multi-objective linear fractional programming method should be recommended to farmers.
 

Keywords

References

Amirnejad H and Bahmanpuri S. 2013. Integration of environmental and economic objectives of agricultural operators in determining the optimal model of cultivation; a case study: Beyza plain of Fars province. Agricultural Economics Research, 5(18): 117-1129. (In Persian).
Abdeshahi A, Mardani Najafabadi M and Zeinali M. 2019. Application of multi-objective fuzzy nonlinear programming model to determining the optimal cropping pattern of crop production in Molathani County. Research report, Agriculture Sciences and Natural Resources, University of Khuzestan. No. 112.411.1. (In Persian).
Anagnostopoulos KP and Petalas C. 2011. A fuzzy multicriteria benefit–cost approach for irrigation projects evaluation. Agricultural Water Management, 98(9): 1409-1416.
Beh EHY, Zheng F, Dandy GC, Maier HR and Kapelan Z. 2017. Robust optimization of water infrastructure planning under deep uncertainty using Meta models. Environmental Modelling & Software. 93: 92-105.
Bell S and Morse S. 2008. Sustainability indicators: Measuring the imeasurable? Second Edition, Earthscan.
Ben-Tal A and Nemirovski A. 1999. Robust solutions of uncertain linear programs. Operations Research Letters, 25(1):1-13.
Bertsimas D and Sim M. 2004. The price of robustness. Operations Research. 52(1): 35-53.
Bohle C, Maturana S & Vera J. 2010. A robust optimization approach to wine grape harvesting scheduling. European Journal of Operational Research, 200(1): 245-252.
Caballero R and Hernández M. 2004. The controlled estimation method in the multi-objective linear fractional problem. Computers & Operations Research, 31(11): 1821-1832.
Chung G, Lansey K and Bayraksan G. 2009. Reliable water supply system design under uncertainty. Environmental Modelling & Software, 24(4): 449-462.
Filippi C, Mansini R and Stevanato E. 2017. Mixed integer linear programming models for optimal crop selection. Computers & Operations Research, 81: 26-39.
Itoh T, Ishii H and Nanseki T. 2003. A model of crop planning under uncertainty in agricultural management. International Journal of Production Economics, 81–82: 555-558.
Khuzestan Water and Power Organization. 2019. Unpublished reports on Surface Water Resources Qualitative Analysis in Karoon Irrigation and Drainage Networks.
Li YP. Huang GH, Yang ZF and Nie SL. 2008. IFMP: Interval-fuzzy multistage programming for water resources management under uncertainty. Resources, Conservation and Recycling, 52(5): 800-812.
Manos B, Papathanasiou J, Bournaris T and Voudouris K. 2010. A multicriteria model for planning agricultural regions within a context of groundwater rational management. Journal of Environmental Management, 91(7): 1593-1600.
Mardani Najafabadi M, Nikooi A, Ziaei S and Ahmadpour M. 2016. Compilation of regional pattern of Cultivation of garden and crops products in Isfahan Province: Multi-Objective structural programming approach. Journal of Economics and Agricultural Development, 30(3): 188-206. (In Persian).
Mardani Najafabadi M, Ziaee S, Ahmadpour Borazjani M and Nikouei A. 2019. Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study. Agricultural Systems, 173: 218-232.
Mishra B, Nishad AK and Singh SR. 2014. Fuzzy multi-fractional programming for land use planning in agricultural production system. Fuzzy Information and Engineering, 6(2): 245-262.
Pourzand F and Bakhshoode M. 2012. Evaluation of agricultural sustainability in Fars province using compromise programing approach. Agricultural Economics Research, 4(13): 1-19. (In Persian).
Pulido-Velazquez M, Andreu J and Sahuquillo A. 2006. Economic optimization of conjunctive use of surface water and groundwater at the basin scale. Journal of Water Resources Planning and Management. 132(6): 454-467.
Sabouhi M and Mardani Najafbadi M. 2013. Application of robust optimization approach for agricultural water resource management under uncertainty. Journal of Irrigation and Drainage Engineering, 139(7): 571-581.
Tan Q and Zhang T. 2018. Robust fractional programming approach for improving agricultural water-use efficiency under uncertainty. Journal of Hydrology, 564: 1110-1119.
Van Hop N. 2007. Fuzzy stochastic goal programming problems. European Journal of Operational Research, 176(1): 77-86.
Zhang C and Guo P. 2017. A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty. Journal of Hydrology, 553: 735-749.
JOURNAL OF AGRICULTURAL SCIENCE AND SUSTAINABLE PRODUCTION
Volume 30, Issue 1
April 2020
Pages 241-256

Files

Share

How to cite

Statistics