Application of Genetic Algorithm in Determination of Optimal Land use Pattern Corresponding with Sustainable Agriculture: A Case Study of Sari Goharbaran

Subject Areas : Agricultural Economics Research

Khadijeh Abdi Rokni ¹ , Seyed-Ali Hosseini-Yekani ² , Samaneh Abedi ³ , Fatemeh Kashiri Kolaei ⁴

1 - M.A. in Agricultural Economics, Sari University of Agricultural Science and Natural Resources, Sari.
2 - Associate Professor, Department of Agricultural Economic, Sari Agricultural Science and Natural Resources University
3 - Assistant Professor, Department of Agricultural Economic, Sari University of Agricultural Science and Natural Resources.
4 - PHD Student in Agricultural Economics, Sari University of Agricultural Science and Natural Resources.

Received: 2018-03-27 Accepted : 2018-12-29 Published : 2021-10-23

Keywords: Genetic Algorithm, Cropping Pattern, Sustainable Agriculture, Non-Linear Programming, Sari Goharbaran,

Abstract :

Introduction:Agriculture as one of the basic pillars of development, has an important role in economic development.  Accordingly,  using cropping pattern optimization is a proper way for agricultural development. Therefore, in the present study, optimal cropping pattern in Goharbaran region of Sari city has been evaluated in terms of multi-objective planning has been done using non-linear programming and genetic algorithm and finally compared each other.
Materials and Methods:Required data for this study has been collected with interview 250 of farmers during the 2014-2015.
Findings:Comparison The results of this study showed that the optimal pattern of non-linear genetic algorithm is superior compared to ordinary non-linear programming model. Because increasing the profit of the genetic algorithm is about 0.2% higher than normal nonlinear planning, while reduced risk the by about 6 percent. Also, the amount of production increases by about 18 percent in the genetic algorithm and the consumption of chemical fertilizer is 7 percent lower than normal nonlinear programming. Based on the results, all four sustainable farming objectives in the framework of multi-objective model in the model obtained from the genetic model have a superiority to the typical nonlinear planning model.
Conclusion:Since the proposed cropping pattern of genetic algorithm causes to increase farmers' gross margin compared to the ordinary nonlinear programming, therefore, the government's encouragement and support is mandatory of the farmers in applying the results of such models.

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