Clustering Target Countries of Iranian Pistachio Exports Based on Hybrid Meta-Heuristic Algorithms
The main objective of this research was to design a model for assessing and partitioning the international pistachio market in order to identify Iran's opportunities in these markets. Accordingly, in this paper, the study of market structure, the status of competitors in the market, market access, and the cultural and political adaptation of countries for the years 2001- 2016 provide indicators for clustering target markets in these markets. Subsequently, using international meta-clustering methods, international pistachio market segmentation has been done and homogeneous export clusters have been extracted for Iran's target markets. In this research, using Cummins clustering algorithm, Cummins and Clooney Antes algorithm and also Cummins and hierarchy combination algorithms for clustering of target countries of Iranian export of pistachio were studied. Comparison of the results of the three clustering methods showed that in the Cummins and hierarchical combination algorithms, the resulting clusters display less error. Based on the results of the Davis-Bouldin, Chu-Su, five clusters were identified for Iran's export destination countries for export of pistachios, and the same policy for the countries in each cluster and policy in the target countries of different clusters could lead to increased efficiency of the considered strategies.
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