Application of Ant Colony Algorithm for Cropping Pattern Optimization (Shahdad, Kerman City)

Introduction The optimized cropping pattern can not only sustainably preserve water resources but bring more income as well. Therefore, since no research has been done on optimizing cropping pattern in the Shahdad county, this study identifies the optimized cropping pattern in this region with the goal of both maximizing farmers' gross profit and decreasing water consumption. Materials and Method Since more than 90 percent of the current cropping pattern in Shahdad is cultivated with the four following crops: irrigated barley and wheat, garlic, and Alfalfa, the needed data were collected during 2016-17 crop year, from 450 farmers who cultivate these four crops simultaneously. 106 farmers were selected for face-to-face interview by using questionnaire and based on simple random sampling. The ant colony meta-heuristic model based on binary knapsack problem to achieve the optimized cropping pattern was used. Results and Discussion The ACO algorithm showed that the cultivated area of irrigated barley, irrigated wheat, garlic, and Alfalfa changed from 509, 408, 617, and 1124 Ha in the observed cropping pattern to 421, 588, 998 and 651 Ha in the optimized cropping pattern, respectively. Therefore, the gross profit, by 282.96%, has increased from 201.59 billion Rials in the observed cropping pattern to 772 billion Rials in the optimal cropping pattern. Suggestion Results showed that optimized cropping pattern in addition to saving 5% of water consumption, will increase gross profit to 282.96%. Therefore, it is suggested to change cropping pattern based on results of this study. JEL Classification: C02, C61, D61, E21