IDEAS home Printed from https://ideas.repec.org/a/eee/agisys/v173y2019icp218-232.html
   My bibliography  Save this article

Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study

Author

Listed:
  • Mardani Najafabadi, Mostafa
  • Ziaee, Saman
  • Nikouei, Alireza
  • Ahmadpour Borazjani, Mahmoud

Abstract

The economic, technical and strategic factors are the three most important factors in examining the cropping patterns in Iran. Iran is geographically located in a part of the planet with specific climate constraints. Drought is one of the constraints that has been a major challenge to agricultural development for many years and has always been the subject of discussions and investigations. On the other hand, constraints such as agricultural soils, economic factors, climate change, agricultural workforce, etc., multiply the production challenges in the country. Despite such constraints, planning a coherent and targeted program for the cultivation of crops and overcome the existing problems is inevitable. The present study introduced a model for optimization of regional cropping pattern decisions, which is one of the subsets of the Multi-Objective Structural Planning (MOSP) approach, and addressed different objectives, such as economic, social and environmental objectives, separately and jointly. However, it is important to address the exchange of crops in different areas in order to achieve the fundamental objectives of determining the optimal cropping pattern. Therefore, in the proposed model of optimal regional cropping pattern, issues such as the transportation of crops and, consequently, virtual water and energy exchanges were also considered. In order to evaluate the proposed model, agricultural arable lands located in the political-geographic divisions of 23 counties of Isfahan province (Iran) were selected for examination. The results showed that in the main groups of grains and forage, a significant reduction was observed in the optimal crop area of the multi-objective model by 26% and 5%, respectively. Increasing the crop area of horticultural products by 10% in the optimal pattern of multi-objective model was another important factor in the analysis of the results. In general, in order to achieve the economic, social and environmental objectives mentioned in this study within the framework of a multi-objective planning, a 16% reduction in the level of the crop area in Isfahan province is inevitable. The results of this measure are reduction in the irrigation water consumption by 17%, increase in the profit by 58% and increase in the production by 11%. Regarding the fact that in the structural planning of cropping pattern, different and sometimes conflicting objectives are considered and the compromise between the objectives is possible in the multi-objective structural planning model, the decision makers are recommended to use this model.

Suggested Citation

  • Mardani Najafabadi, Mostafa & Ziaee, Saman & Nikouei, Alireza & Ahmadpour Borazjani, Mahmoud, 2019. "Mathematical programming model (MMP) for optimization of regional cropping patterns decisions: A case study," Agricultural Systems, Elsevier, vol. 173(C), pages 218-232.
    • Handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:218-232
    DOI: 10.1016/j.agsy.2019.02.006
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308521X18306644
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agsy.2019.02.006?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Biswas, Animesh & Pal, Bijay Baran, 2005. "Application of fuzzy goal programming technique to land use planning in agricultural system," Omega, Elsevier, vol. 33(5), pages 391-398, October.
    2. Venables, Anthony J. & Limao, Nuno, 2002. "Geographical disadvantage: a Heckscher-Ohlin-von Thunen model of international specialisation," Journal of International Economics, Elsevier, vol. 58(2), pages 239-263, December.
    3. ,, 2000. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 16(2), pages 287-299, April.
    4. Pennington, Derric N. & Dalzell, Brent & Nelson, Erik & Mulla, David & Taff, Steve & Hawthorne, Peter & Polasky, Stephen, 2017. "Cost-effective Land Use Planning: Optimizing Land Use and Land Management Patterns to Maximize Social Benefits," Ecological Economics, Elsevier, vol. 139(C), pages 75-90.
    5. de Koeijer, T. J. & Wossink, G. A. A. & Smit, A. B. & Janssens, S. R. M. & Renkema, J. A. & Struik, P. C., 2003. "Assessment of the quality of farmers' environmental management and its effects on resource use efficiency: a Dutch case study," Agricultural Systems, Elsevier, vol. 78(1), pages 85-103, October.
    6. 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.
    7. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    8. Lundberg, Liv & Jonson, Emma & Lindgren, Kristian & Bryngelsson, David & Verendel, Vilhelm, 2015. "A cobweb model of land-use competition between food and bioenergy crops," Journal of Economic Dynamics and Control, Elsevier, vol. 53(C), pages 1-14.
    9. Jones, D. & Barnes, E. M., 2000. "Fuzzy composite programming to combine remote sensing and crop models for decision support in precision crop management," Agricultural Systems, Elsevier, vol. 65(3), pages 137-158, September.
    10. Karami, Ayatollah & Esmaeili, Abdoulkarim & Najafi, Bahadin, 2012. "Assessing effects of alternative food subsidy reform in Iran," Journal of Policy Modeling, Elsevier, vol. 34(5), pages 788-799.
    11. Francisco, Sergio R. & Ali, Mubarik, 2006. "Resource allocation tradeoffs in Manila's peri-urban vegetable production systems: An application of multiple objective programming," Agricultural Systems, Elsevier, vol. 87(2), pages 147-168, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cheng Han & Shengbo Chen & Yan Yu & Zhengyuan Xu & Bingxue Zhu & Xitong Xu & Zibo Wang, 2021. "Evaluation of Agricultural Land Suitability Based on RS, AHP, and MEA: A Case Study in Jilin Province, China," Agriculture, MDPI, vol. 11(4), pages 1-23, April.
    2. Li, Mo & Fu, Qiang & Singh, Vijay P. & Liu, Dong & Li, Tianxiao & Zhou, Yan, 2020. "Managing agricultural water and land resources with tradeoff between economic, environmental, and social considerations: A multi-objective non-linear optimization model under uncertainty," Agricultural Systems, Elsevier, vol. 178(C).
    3. Karner, Katrin & Schmid, Erwin & Schneider, Uwe A. & Mitter, Hermine, 2021. "Computing stochastic Pareto frontiers between economic and environmental goals for a semi-arid agricultural production region in Austria," Ecological Economics, Elsevier, vol. 185(C).
    4. Dariane, A.B. & Ghasemi, M. & Karami, F. & Azaranfar, A. & Hatami, S., 2021. "Crop pattern optimization in a multi-reservoir system by combining many-objective and social choice methods," Agricultural Water Management, Elsevier, vol. 257(C).
    5. Zhang, Zepeng & Wang, Qingzheng & Guan, Qingyu & Xiao, Xiong & Mi, Jimin & Lv, Songjian, 2023. "Research on the optimal allocation of agricultural water and soil resources in the Heihe River Basin based on SWAT and intelligent optimization," Agricultural Water Management, Elsevier, vol. 279(C).
    6. Huihui Zheng & Zhiting Sang & Kaige Wang & Yan Xu & Zhaoyang Cai, 2022. "Distribution of Irrigated and Rainfed Agricultural Land in a Semi-Arid Sandy Area," Land, MDPI, vol. 11(10), pages 1-13, September.
    7. Mostafa Mardani Najafabadi & Abbas Mirzaei & Hassan Azarm & Siamak Nikmehr, 2022. "Managing Water Supply and Demand to Achieve Economic and Environmental Objectives: Application of Mathematical Programming and ANFIS Models," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(9), pages 3007-3027, July.
    8. Yuxiang Ma & Min Zhou & Chaonan Ma & Mengcheng Wang & Jiating Tu, 2021. "Hybrid Economic-Environment-Ecology Land Planning Model under Uncertainty—A Case Study in Mekong Delta," Sustainability, MDPI, vol. 13(19), pages 1-22, October.
    9. Nikouei, Alireza & Asgharipour, Mohammad Reza & Marzban, Zahra, 2022. "Modeling land allocation to produce crops under economic and environmental goals in Iran: a multi-objective programming approach," Ecological Modelling, Elsevier, vol. 471(C).
    10. Mostafa Mardani Najafabadi & Niloofar Ashktorab, 2023. "Mathematical programming approaches for modeling a sustainable cropping pattern under uncertainty: a case study in Southern Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9731-9755, September.
    11. Mardani Najafabadi, Mostafa & Magazzino, Cosimo & Valente, Donatella & Mirzaei, Abbas & Petrosillo, Irene, 2023. "A new interval meta-goal programming for sustainable planning of agricultural water-land use nexus," Ecological Modelling, Elsevier, vol. 484(C).
    12. Ana Esteso & M. M. E. Alemany & Angel Ortiz & Shaofeng Liu, 2022. "Optimization model to support sustainable crop planning for reducing unfairness among farmers," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(3), pages 1101-1127, September.
    13. Nouri, Milad & Homaee, Mehdi & Pereira, Luis S. & Bybordi, Mohammad, 2023. "Water management dilemma in the agricultural sector of Iran: A review focusing on water governance," Agricultural Water Management, Elsevier, vol. 288(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenqing Chen & Melvyn Sim & Jie Sun & Chung-Piaw Teo, 2010. "From CVaR to Uncertainty Set: Implications in Joint Chance-Constrained Optimization," Operations Research, INFORMS, vol. 58(2), pages 470-485, April.
    2. Stefan Mišković, 2017. "A VNS-LP algorithm for the robust dynamic maximal covering location problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 39(4), pages 1011-1033, October.
    3. M. J. Naderi & M. S. Pishvaee, 2017. "Robust bi-objective macroscopic municipal water supply network redesign and rehabilitation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(9), pages 2689-2711, July.
    4. Ruiwei Jiang & Siqian Shen & Yiling Zhang, 2017. "Integer Programming Approaches for Appointment Scheduling with Random No-Shows and Service Durations," Operations Research, INFORMS, vol. 65(6), pages 1638-1656, December.
    5. Mínguez, R. & García-Bertrand, R., 2016. "Robust transmission network expansion planning in energy systems: Improving computational performance," European Journal of Operational Research, Elsevier, vol. 248(1), pages 21-32.
    6. Dimitris Bertsimas & Agni Orfanoudaki, 2021. "Algorithmic Insurance," Papers 2106.00839, arXiv.org, revised Dec 2022.
    7. Rafael Epstein & Andres Neely & Andres Weintraub & Fernando Valenzuela & Sergio Hurtado & Guillermo Gonzalez & Alex Beiza & Mauricio Naveas & Florencio Infante & Fernando Alarcon & Gustavo Angulo & Cr, 2012. "A Strategic Empty Container Logistics Optimization in a Major Shipping Company," Interfaces, INFORMS, vol. 42(1), pages 5-16, February.
    8. Zhang, Wei & (Ato) Xu, Wangtu, 2017. "Simulation-based robust optimization for the schedule of single-direction bus transit route: The design of experiment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 106(C), pages 203-230.
    9. Enrico Bartolini & Dominik Goeke & Michael Schneider & Mengdie Ye, 2021. "The Robust Traveling Salesman Problem with Time Windows Under Knapsack-Constrained Travel Time Uncertainty," Transportation Science, INFORMS, vol. 55(2), pages 371-394, March.
    10. Antonio G. Martín & Manuel Díaz-Madroñero & Josefa Mula, 2020. "Master production schedule using robust optimization approaches in an automobile second-tier supplier," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 143-166, March.
    11. Hamed Mamani & Shima Nassiri & Michael R. Wagner, 2017. "Closed-Form Solutions for Robust Inventory Management," Management Science, INFORMS, vol. 63(5), pages 1625-1643, May.
    12. Shunichi Ohmori, 2021. "A Predictive Prescription Using Minimum Volume k -Nearest Neighbor Enclosing Ellipsoid and Robust Optimization," Mathematics, MDPI, vol. 9(2), pages 1-16, January.
    13. Hanks, Robert W. & Weir, Jeffery D. & Lunday, Brian J., 2017. "Robust goal programming using different robustness echelons via norm-based and ellipsoidal uncertainty sets," European Journal of Operational Research, Elsevier, vol. 262(2), pages 636-646.
    14. Roberto Gomes de Mattos & Fabricio Oliveira & Adriana Leiras & Abdon Baptista de Paula Filho & Paulo Gonçalves, 2019. "Robust optimization of the insecticide-treated bed nets procurement and distribution planning under uncertainty for malaria prevention and control," Annals of Operations Research, Springer, vol. 283(1), pages 1045-1078, December.
    15. Soyster, A.L. & Murphy, F.H., 2013. "A unifying framework for duality and modeling in robust linear programs," Omega, Elsevier, vol. 41(6), pages 984-997.
    16. Li, Ping & Han, Yingwei & Xia, Yong, 2016. "Portfolio optimization using asymmetry robust mean absolute deviation model," Finance Research Letters, Elsevier, vol. 18(C), pages 353-362.
    17. Lee, In Gyu & Yoon, Sang Won & Won, Daehan, 2022. "A Mixed Integer Linear Programming Support Vector Machine for Cost-Effective Group Feature Selection: Branch-Cut-and-Price Approach," European Journal of Operational Research, Elsevier, vol. 299(3), pages 1055-1068.
    18. Mohsen Jalalimajidi & SM Seyedhosseini & Ahmad Makui & Masoud Babakhani, 2018. "Developing a comprehensive model for new energy replacement in the country’s development program using a robust optimization approach," Energy & Environment, , vol. 29(6), pages 868-890, September.
    19. Wang, Tian & Deng, Shiming, 2019. "Multi-Period energy procurement policies for smart-grid communities with deferrable demand and supplementary uncertain power supplies," Omega, Elsevier, vol. 89(C), pages 212-226.
    20. Kuhn, K. & Raith, A. & Schmidt, M. & Schöbel, A., 2016. "Bi-objective robust optimisation," European Journal of Operational Research, Elsevier, vol. 252(2), pages 418-431.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agisys:v:173:y:2019:i:c:p:218-232. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agsy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.