تعیین الگوی بهینۀ زراعی شهرستان اسفراین (کاربرد برنامه ریزی فازی با ارزش بازه ای بر اساس برش های آلفای نامحدود)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس ارشد اقتصاد کشاورزی دانشگاه فردوسی مشهد

2 استادیار گروه اقتصاد کشاورزی دانشگاه فردوسی مشهد

3 استاد گروه اقتصاد کشاورزی دانشگاه فردوسی مشهد

چکیده

با توجه به ماهیت ویژة فعالیت­های کشاورزی و تأثیرگرفتن نتایج تصمیمات از ریسک و حتمیت‌نداشتن این فعالیت­ها، درنظرگرفتن ریسک به هنگام برنامه­ریزی در بخش کشاورزی امری ضروری است. در مطالعة حاضر، برای لحاظ‌کردن شرایط نبودن قطعیت و همچنین تأکید بر محدودیت منابع آب در تعیین الگوی بهینة زراعی، از روش برنامه‌ریزی فازی با ارزش بازه­ای استفاده شد. آمار و اطلاعات مورد نیاز از طریق جمع‌آوری 128 پرسشنامه و مصاحبة حضوری با کشاورزان شهرستان اسفراین به‌صورت نمونه­گیری تصادفی ساده، در سال زراعی 1391-1392 تهیه شد. نتایج نشان می­دهد محصولات ذرت علوفه­ای، لوبیا قرمز و گندم محصولات بهینه و اقتصادی برای کشت در اکثر سناریوهاست و سود الگوی بهینه با کاهش نبودن قطعیت منابع آب افزایش می­یابد. همچنین، میزان استفاده از آب در الگوی کشت فعلی بیش از مقدار مصرف آب در الگوی کشت بهینه است؛ بنابراین، پیشنهاد می­شود با ارائة سیاست­های حمایتی توسط مسئولان کشاورزی شهرستان مذکور، مانند تقویت سطح پوشش بیمة محصولات کشاورزی یا قیمت تضمینی برای کشت محصولات بهینة پیشنهادی گسترش یابد تا ضمن افزایش سودآوری کشاورزان، از برداشت بیش از حد از سفره‌‌های آب زیرزمینی نیز جلوگیری شود.

کلیدواژه‌ها

عنوان مقاله [English]

Determine the optimal cropping pattern of Esfarayen county (Application of interval-valued fuzzy programming based on infinite alpha-cuts)

نویسندگان [English]

  • Mahsa Bahrami Nasab 1
  • Arash Dourandish 2
  • Naser Shahnoushi 3
  • Mohamad Reza Kohansal 3
1 MSc., Faculty of Agriculture, Ferdousi University of Mashhad, Iran
2 Assistant Professor, Faculty of Agriculture, Ferdousi University of Mashhad, Iran
3 Professors, Faculty of Agriculture, Ferdousi University of Mashhad, Iran
چکیده [English]

Due to the special nature of agricultural activities and results of decisions influenced by the risk and uncertainty of these activities, consideration risk is essential in planning for agriculture sector. Interval-valued fuzzy programming approach is advantage of in this study for considering the conditions of uncertainty and additionally emphasizing on the limitation of water resources in defining the optimal crop pattern. The required data was gathered via 128 questionnaire and interviews with the farmers of Esfarayen county as simple random sampling in 2012-2013. The results show that Forage maize, Red beans and wheat in the most case scenarios are economical as well as optimal crops for cultivation, and the profit of the optimul model increases with reduction the uncertainty in water resources. Also, the level of water consumption in current cropping patterns is more than the amount of water consumption in the optimal cropping pattern. Therefore, presentation of supportive policies such asenhancement of insurance coverage for crops or the guaranteed price for crops, cultivationof the recommended optimal crops are suggested to develop. In addition, the increase inprofitability of the farmers from too much usage of underground aquifers is stopped aswell.

کلیدواژه‌ها [English]

  • α-cut
  • Fuzzy programming
  • interval-valued
  • uncertainty
  • water resources

مراجع

  1. Agriculture- Jehad of Northern Khorasan. (2012) Yearbook of Plant Production Statistics. from http:// boe.nkj.ir.
  2. Berim-nejad, V. & Paykani, GH. (2004). The Effects of Irrigation Efficiency Improvement in Agricultural Section on Increasing level of Ground water, Development and Agricultural Economic, 12(47), 69-95. (In Farsi).
  3. Biswas, A., & Baranpal, B. (2005). Application of fuzzy goal programming technique to land use planning in agricultural system, The International Journal of Management Science, 33 (5), 391-398.
  4. Chen, C., Huang, G.H., Li, Y.P., & Zhou, Y. (2012). A robust risk analysis method for water resources allocation under uncertainty. Stoch Environ Res Risk Assess, published online: 28 August 2012.
  5. Fan, Y.R., Huang, G.H., Guo, P., & Yang, A.L. (2012). Inexact two-stage stochastic partial programming: application to water resources management under uncertainty. Stoch Environ Res Risk Assess, 26, 281–293.
  6. Ghorbanian, E., Zibaie, M., Ghorbani, M., & Kohansal, M. (2013). Determine the Optimal Cropping Pattern Due to Llimited Groundwater Resources in Kavar Plain. Agricultural Economics and Development, 27(1), 1-7. (In Farsi).
  7. Gorzalezang, M.B. (1987). A method of inference in approximate reasoning based on interval-valued fuzzy sets, Fuzzy Sets and Systems, 21,  1-17.
  8. Guo, P., Huang, G.H., Zhu, H., & Wang, X.L. (2010). A two-stage programming approach for water resources management under randomness and fuzziness. Environmental Modelling & Software, 25, 1573-1581.
  9. Guo, R. INTERVAL-VALUED FUZZY SET MODELLING OF SYSTEM RELIABILITY. From web.uct.ac.za/depts/stats/rguo_files/rguo_09.pdf‎
  10. Hosseinzadeh, M., Kohansal, M.R., & Ghorbani, M. (2013). Evaluate the Effects of Targeting Subsidies on Cultivation Pattern in the Esfarayen County (Interval Programming Approach). Agricultural Economics and Development, 27 (1), 64-74. (In Farsi).
  11. Huang, Y., Li, Y.P., Chen, X., & Ma, Y.G. (2012). Optimization of the irrigation water resources for agricultural sustainability in Tarim River Basin, China. Agricultural Water Management, 107, 74– 85.
  12. IWMI. (2003). Water productivity in agriculture: Limits and  Opportunities for Improvements, Press Release: New research findings offer hope for the world water crisis, Nairobi November 3. 
  13. Kaur,  B., Sidhu, R.S., & Vatta, K. (2010). Optimal Crop Plans for Sustainable Water Use in Punjab. Agricultural Economics Research Review. 23, 273-284.
  14. Li, Y.P., Huang, G.H., Nie, S.L. & Chen, X. (2011). A robust modeling approach for regional water management under multiple Uncertainties. Agricultural Water Management, 98, 1577– 1588.
  15. Li,  Y.  P.,  Huang,  G.  H.  and  Zhou,  H.  D.  (2009).  A  multistage  fuzzy stochastic  programming model  for  supporting  water  resources allocation  and  management. Environmental Modelling  and Software, 24, 786-797.
  16. Lu, HW., Huang, G.,  He, L. (2011). An inexact rough-interval fuzzy linear programming method for generating conjunctive water-allocation strategies to agricultural irrigation systems. Applied Mathematical Modelling, 35, 4330–4340.
  17. Lu H.W., Huang, G.H., He, L. (2010). Development of an interval-valued fuzzy linear programming method based on infinite α-cuts for water resources management, Environmental Modelling & Software. 25, 354–361.
  18. Lu, HW., Huang, GH., He, L. (2009). A semi-infinite analysis-based inexact two-stage stochastic fuzzy linear programming approach for water resources management. Eng Optim , 41,73–85.
  19. Mansouri, H., Kohansal, M.R., Khadem Ghousi, M.F. (2009). Introducing a lexicographic goal programming for environmental conservation program in farm activities: A case study in iran. China Agricultural Review, 1 (4), 478-484.
  20. Mardani,  M., Sakhdari, H., & Sabouhi, M. (2011). Application of multi-objective planning and control parameters of conservatism in agricultural planning. Case study: Mashhad city. AgriculturalEconomicsResearch, 3(2), 163-180. (In Farsi).
  21. Mortazavi, A., Azhdari, S. & Mousavi, H. (2011). Determining the optimal crop pattern and Market orientation under uncertainty in Arjan in Fars province, the application of two-stage stochastic programming model. Agricultural Economics, 5(3), 75-94. (In Farsi).
  22. Mohammadi, H., Bostani, F., & Kafilzadeh, F. (2012). Optimal Cropping Pattern Using a Multi-objectives Fuzzy Non-linear Optimization Algorithm: A Case Study. Water & wastewater, (4), 43-55. (In Farsi).
  23. Mohammadi, Y., Shabanali Fami, H., & Asadi, A. (2010).Evaluation of farmers' skills in the use of agricultural water management technologies in the city of Zarrin Dasht, Fars Province. Iranian journal of Agricultural Economics and Development Research, 41(4), 501-511. (In Farsi).
  24. Mohammadi, Y., Shabanali Fami, H., & Asadi, A. (2009). Analysis of Effective components on Agricultural Water Management in Zarindasht County from Farmers viewpoint. Journal of Agricultural Science & Natural Resourses, 16 (2). (In Farsi).
  25. Rastegaripour, F., & Sabouhi Sabouni, M. (2012). Grey Fractional Programming, A New Experimental Approach in Sustainable Agriculture. Journalofsustainable Agricultural andproduction Science, 22(1), 127-135. (In Farsi).
  26. Sabouhi Sabouni, M., & Mardani, M. (2013). Reliable Water Supply System Design under Uncertainty Case Study: Zayandehroud River Basin. Water & wastewater, 3, 33-44. (In Farsi).
  27. Sabouhi, M., & Mardani, M. (2011). Evaluate The effect of rainfall on crop pattern and total gross within the scope of irrigation network of diversion Dam right hand Nkouabad. Agricultural Economics, 5(3): 209-228. (In Farsi).
  28. Sengupta, A., Kumar Pal, T., & Chakraborty, D. (2001). Interpretation of inequality constraints involving interval coefficients and a solution to interval linear programming. Fuzzy Sets and Systems, 119(1), 129-138.
  29. Soil Water Management Research Group. (2005). Experiences with micro agricultural technologies: Tanzania, Sokine University of Agriculture. Department of Agricultural Engineering and Land Planning, P.12.
  30. Tan, Q., Huang, G.H., & cai, Y.P. (2011). Radial interval chance-constrained programming for agricultural non-point source water pollution control under uncertainty. Agricultural Water Management,  98, 1595– 1606.
  31. Wang, S., & Huang, G.H. (2011). Interactive two-stage stochastic fuzzy programming for water resources management.  Journal of  Environmental Management, 92, 1986-1995.
  32. XieTing,  Z.,  ShaoZhong,  K.,  FuSheng,  L.,  Lu,  Zh.,  Ping,  G.  (2010).  Fuzzy  multi-objective  linear programming  applying  to  crop  area  planning.  Agricultural  Water  Management.  98 (1),  134-142..
  33. XU, Y., & Qin, X.S. (2010). Agricultural effluent control under uncertainty: An inexact double-sided fuzzy chance-constrained model. Advances in Water Resources, 33, 997-1014.
  34. Zhang, X ., Huang, G.H., Nie, X., & Lin, Q. (2011). Model-based decision support system for water quality management under hybrid uncertainty .Expert Systems with Applications,  38: 2809–2816.

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