الگوی بهینه‌ی کشت مبتنی بر معیارهای چندگانه‌ی اقتصادی، منطقه‌ای و پایداری کشاورزی در شهرستان ساری؛ کاربرد الگوی تلفیقی AHP و برنامه‌ریزی خطی

نوع مقاله : مقالات پژوهشی

نویسندگان

• اسماعیل فلاحی ¹
• سپیده قلی نژاد ²

¹ دانشگاه شیراز

² دانشگاه آزاد اسلامی، قائمشهر

https://doi.org/10.22067/jead2.v30i1.46040

چکیده

تدوین الگوی مناسب کشت محصولات به عنوان یکی از مهم‌ترین رسالت‌های برنامه‌ریزان، مستلزم تصمیم‌سازی دقیق و واقع‌بینانه بر اساس اهداف و معیارهای مختلف در راستای تأمین منافع کل مجموعه‌ی ذی نفع کشاورزی در بلندمدت است. مطالعه‌ی حاضر با هدف بازنگری در الگوی رایج بهره‌برداران شهرستان ساری و تدوین الگوی کشتی که معیارهای چندگانه‌ی منطقه‌ای و پایداری کشاورزی را در کنار ملاحظات اقتصادی مداخله داده، الگوی تلفیقی AHP و مدل برنامه‌ریزی خطی را به کار بست. بدین منظور، پس از طراحی مدل سه سطحی AHP، بردار وزن نهایی خروجی مدل AHP برای محصولات مختلف به عنوان ورودی ضرایب تابع هدف در الگوی برنامه‌ریزی خطی وارد شده و مدل مورد نظر در فضای محدودیت‌های حاکم حل گردید. نتایج حاصل از الگوی بهینه‌ی کشت در مدل تلفیقی، ضمن توصیه‌ی تغییراتی در شیوه‌ی توزیع سطح زیرکشت بین محصولات، میزان سود را نیز به میزان 63/3 درصد نسبت به الگوی رایج منطقه افزایش داد. مقایسه‌ی نتایج الگوی تلفیقی با سناریویی که تنها هدف بیشینه‌سازی منافع اقتصادی را دنبال می‌کند، نشان داد که چشم‌پوشی از مقدار مشخصی سود (به میزانی کم‌تر از 8 درصد) در الگوی بهینه، امکان توجه و دخالت دادن معیارهای مهم دیگری را از جمله سازگاری محصول با شرایط اقلیمی منطقه‌ای، میزان مصرف آب، تأثیرات زیست‌محیطی کشت محصول، اشتغال‌زایی، مهارت و تخصص مورد نیاز برای عمل‌آوری محصول و میزان ریسک کشت محصول که در وضعیت فعلی کشاورزی بسیار حیاتی بوده و دارای اثرات قابل توجه در بلندمدت است، فراهم می‌آورد. بر این اساس، پیشنهاد می‌شود الگوی بهینه‌ی کشت مورد نظر در سطح منطقه یا دست‌کم به‌صورت پایلوت در بخش‌هایی از شهرستان اجرا شود.

کلیدواژه‌ها

• الگوی بهینه‌ی کشت
• برنامه‌ریزی‌ خطی
• پایداری کشاورزی
• فرایند تحلیل سلسله‌ی مراتبی ((AHP
• مزیت‌های منطقه‌ای
• ملاحظات اقتصادی

20.1001.1.20084722.1395.30.1.4.9

عنوان مقاله [English]

Optimal Cropping Pattern Based on Multiple Economic, Regional, and Agricultural Sustainability Criteria in Sari, Iran: Application of a Consolidated Model of AHP and Linear Programming

نویسندگان [English]

• E. Fallahi ¹
• S. Gholinezhad ²

¹ Shiraz University

² Islamic Azad University, Ghaemshahr

چکیده [English]

Introduction: Determining a suitable cropping pattern is an important task for planners and requires an exact and realistic decision-making process based on several goals and criteria corresponding to secure the interest of agricultural beneficiaries in long-term. Accordingly, this study reviews the current pattern operated by farmers in Sari, Iran, and intends to provide a cropping pattern that considers the multifold regional and agricultural sustainability criteria along with economic considerations.
Materials and Methods: In order to achieve the study goals, a consolidated model of AHP and Linear Programming was applied. For this purpose, we constructed a three-level AHP, including a goal (determining the weight of each crop), seven criteria, and seven alternatives. Profitability, compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop were considered as the criteria in the model. Seven alternative crops including rice, wheat, rapeseed, barley, soybean, clover, and vegetables were considered too. The next step is determining the weight of each criterion with regard to the goal and the weight of each alternative with regard to each criteria. By multiplying these weights, final weights for various crops were obtained from the model. Derived weights for each crop were then applied as objective function coefficients in the Linear Programming model and the model was solved subject to the constraints.
Results and Discussion: Optimal cropping pattern determined based on the consolidated model of AHP and Linear Programming and the results compared to a scenario that only looks forward to maximizing the economic interests. Due to the low profitability of rapeseed and barley, these crops eliminated from the pattern in the profit-maximizing scenario. According to the results, the scenario provides 11.36% more profit than the current cropping pattern. In the consolidated model, we first calculated final weight for any crop. With a relative weight of 0.23, rice had the highest priority. Wheat, vegetables, clover, barely, rapeseed, and soybean weighed 0.17, 0.16, 0.14, 0.11, 0.1, 0.09 and took the respective priorities. In the next step, we use the weights for each crop as objective function coefficients in the Linear Programming model and solve the model subject to the constraints. Rice cultivation had the largest crop area with 15126 ha (62.52% of the entire crop area). Clover, vegetables, wheat, rapeseed, barely, and soybean stood behind the rice. Comparing the ideal cropping pattern, which was based on multifold criteria, with the current pattern showed that the most significant changes between the patterns occurred for wheat, soybean, and rapeseed crops so the recommended crop area for wheat in the optimal pattern increased by around 165% , however, the recommended crop area for soybean and rapeseed decreased by 96% and 75% respectively. The total profit of the ideal cropping pattern was 1,152,469,874,210 Rials. This shows that the optimal pattern caused an increase in profit by 3.63% compared to the current cropping pattern. Comparison between the results of consolidated model and profit-maximizing scenario shows that the optimal cropping pattern recommended by the consolidated model offers lower profits (lower than 8%) than the pattern offered by profit-maximizing model, however, the optimal pattern allows us to take other important criteria into account, including crop compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop.
Conclusion: Using a consolidated model of AHP and Linear Programming, this study aimed to decide an optimal cropping pattern that considers the multifold regional and agricultural sustainability criteria beside economic considerations in Sari. The results of ideal cropping pattern in consolidated model recommended some changes distribute cropping area between crops and increased the profit compared to the current pattern. Comparison between the results of consolidated model and a scenario that only looks forward to maximizing the economic benefits shows that the ideal cropping pattern recommended by the consolidated model offers lower profits (lower than 8%) than the pattern offered by profit-maximizing scenario, however, the optimal pattern allows us to take other important criteria into account, including crop compatibility with regional and geographical conditions, water consumption, environmental effects of cropping, job creation opportunities, skill and proficiency required for producing a crop, and risk taken to cultivate a crop, which are so vital in current agricultural situation and result in significant long-term effects. Therefore, it is recommended to have the optimal cropping pattern operated in the region or at least, in parts of the district as a pilot project.

کلیدواژه‌ها [English]

• Agricultural Sustainability
• AHP (Analytic Hierarchy Process)
• Economic Considerations
• Linear programming
• Optimal cropping pattern
• Regional Advantages

مراجع

1- Agha S. R., Nofal L. G., Nassar H. A., and Shehada R. Y. 2012. Multi criteria governmental crop planning problem: an analitic hierarchy approach. Management. 2(4): 96-105.

2- Akbari N., and Zahedi K. 2008. Fuzzy multi attribute decision making and its application in determining optimal cropping pattern in farms. Journal of Agricultural Economics. 2(4): 21-36. (in Persian).

3- Albodvi A., Chaharsooghi K., and Esfahanipour A. 2007. Decision making in stock trading: an application of PROMETHEE. European Journal of Operational Research. 177(1): 673-683.

4- Alvanchi M., and Sabouhi M. 2007. The application of differential multi-criteria decision making in agricultural planning: a case study of Fars Province. MSc thesis, University of Zabol. (inPersian).

5- Amini Faskhoudi A., Nouri H., and Hejazi R. 2008. Determining optimal cropping pattern in Eastern Isfahan's farms using goal programming approach. Journal of Agricultural Economics. 2(4): 177-197. (in Persian).

6- Aras A. 1988. Agricultural accounting.Publication of Aegean University. 486. (in Turkish).

7- Asadi H., and Soltani Gh. 2000.Investigating the safety margin and determining the optimal cropping pattern using linear programming method.Journal of Agricultural Economics and Development. 31: 71-86. (in Persian).

8- Azar A., and Rajabzadeh A. 2009.Applied decision making (M.A.D.M. Approach). Third edition, Negah-e-Danesh Press. Tehran. (in Persian).

9- Baniasadi M., and Zare Mehrjerdi M. R. 2010. Studying the effects of optimal cultivation pattern on rural poverty: Case study of Orzoo,iyeh district in Baft (Kerman- Iran).Journal of Agricultural Economics. 2(4): 183-209. (in Persian).

10- Baradaran Sirjani F., Kohansal M., and Sabouhi M. 2014. Application of two-stage multi-objective fuzzy linear programming model to determine cropping pattern; a case study of central part of Mashhad.Journal of Agricultural Economics and Development. 28(4): 376-368. (in Persian).

11- Biswas A., and Pal B. B. 2004. Application of fuzzy goal programming technique to land use planning in agricultural system, omega. The International Journal of Management Science. 33(5):391-398.

12- Daneshvar Kakhaki M., Sahnoushi N., Salehi F., and Abedi R. 2009. The determiation of optimal crop pattern with aim of reduction in hazards of envirenmental.American Journal of Agricultural and Biological Sciences. 4(4): 305-310.

13- Dodangeh J., Rosnah M.Y., Napsiah I., Yusof I., Beik Zadeh M., and Jassbi J. 2011. Designing fuzzy multi criteria decision making model for best selection of areas for improvement in EFQM (European Foundation for Quality Management) model. African Journal of Business Management. 5(12): 5010-5021.

14- Fallahi E., Khalilian S., and Ahmadian M. 2013.Optimizing cropping pattern with emphasis on water resource restrictions; A case study of Seydan-Farough Plain, Marvdasht, Iran. Journal of Agricultural Economics Research. 5(2): 91-115. (in Persian).

15- Feizabadi Y., Yousefpour F., and Asadpour H. 2012. Application of multi attribute fuzzy linear programming model to determine optimal cropping pattern of rice varieties in Babolsar paddy fields. Journal of Agricultural Economics. 8(1): 31-45. (in Persian).

16- Francisco S. R., and Ali M. 2006. Resource allocation tradeoffs in Manilaʼs peri-urban vegetable production systems: an application of multiple objective programming. Agriculture Systems. 87: 147-168.

17- Itoh T., Shii H. I., and Nanseki T. 2003. Model of cropplanning under uncertainty in agricultural management.International Journal of Production Economics. 81-82: 555-558.

18- Jihad-e-Agriculture Organization of Mazandaran Province. 2014. (in Persian).

19- Kang S., Zeng x., Li F., Zhang L., and Guo P. 2011. Fuzzy multi- objective linear programming applying to crop area planning. Agricultural Water Management. 98: 134-142.

20- Miao C., He B., and Chen X. 2006. Study on the multiple objective linear planning applied in comprehensive control of small watershedla case study from Mimagou Small Watershed in Shizhu County Sichuan Province. Chinese Journal of Economics Agricultural. 14(3): 223-227.

21- Mohammadian F., Shahnoushi N., Ghorbani M., and Aghel H. 2011. Selecting potential cropping pattern based on Analytical Hierarchy Process (AHP); a case study of Torbat-e-Jaam plain.Journal of Sustainable Agriculture and Production Science. 1(1): 171-187. (in Persian).

22- Mohammadi H., Boustani F., and Kafilzadeh F. 2012. Determining optimal cropping pattern using non-fuzzy multi objective optimization algorithm.Journal of Water and Wastewater. 4:43-55. (in Persian).

23- Mo'meni M. 2006. New issues of Operational Research.First edition. Tehran. University of Tehran. Faculty of Management Press. (in Persian).

24- Oliveira C., and Henggeler C. A. 2007. Multiple objective linear programming models with interval coeffients an illustrated over view.European Journal of Operational Research. 181(3): 1434-1463.

25- Pakdaman M. and Najafi B. 2009. The application of deterministic and fuzzy multi-objective programmingin determining the optimal cropping pattern: a case study of Nilab Plain in Isfahan Province. Journal of Agricultural Economics Research. 1(2): 121-139. (in Persian).

26- Ramanthan R., and Ganesh L. S. 2000. Using AHP for resource allocation problems.European Operational Research. 80: 2-9.

27- Regulwar D. G., and Gurave J. B. 2013.Two-phase multi objective fuzzy linear programming approach for sustainable irrigation planning.Journal of Water Resource and Protection. 5: 642-651.

28- Vivekanandan N., Visvanathan K., and Gupta S. 2009. Optimization of cropping pattern using goal programming approach.Operational Research Society of India. 46(3): 259-274.

29- Yu S., and Zhang J. 2006. Multi-objective programming method for land use based on genetic algoritm. China Population Research and Enviorment. 16(5): 62-66.

30- Zhaleh Rajabi M., Salehi F., and Daneshvar KakhkiM. 2011. Determiningthe optimal groundwater withdrawals using game theory and determining the cropping pattern.The 2nd Iranian national conference on Applied research in water resources. (in Persian).