Model the allocation of productive financial resources from the perspective of livelihood poverty indicators using a combination of clustering methods and SAW technique

Poverty is a social, economic, cultural and political reality that has long been one of the greatest human problems. The diversity of problems, needs and problems of the deprived and low-income groups of the society and the multiplicity of poverty indicators on the one hand, and on the other hand the lack of financial resources and credits to solve the poverty indicators, organizations in charge of poor affairs, including Imam Khomeini Relief Committee Has faced serious challenges in the optimal allocation of resources. Therefore, the aim of the present study is to classify the clients of Tabriz Relief Committee from the perspective of livelihood poverty indicators, ranking these clusters in terms of cost and finally allocating productive and optimal resources for each cluster. In this way, with the least resources, a wide range of the needy benefit from these resources. To do this, with cluster analysis of data extracted from the system, 700 clients of Tabriz Relief Committee have been clustered from the perspective of livelihood poverty indicators and K-mean method. The results of this study were a cluster structure consisting of 10 clusters, which according to the characteristics of the clusters, titles for the clusters were considered. Finally, in order to rank the clusters, a multi-characteristic SAW decision-making method has been used. The research findings show the difference between the effectiveness of allocation in clustering method compared to other traditional methods.