---

The tourism industry has become a major economic activity in the early years of the 21st Century and is considered one of the most productive and most employment-oriented global industries. Tourism is one of the most important factors generating wealth and employment in the world. It is necessary to plan for the proper exploitation of this industry, The most important steps to plan are to locate sites for providing tourists with the services they need in the form of tourist villages, This research is for the city of Shush which is one of the most important tourist areas of Khuzestan province And since it has many ancient monuments, it has attracted many tourists, , But the city has been at a very low level in terms of having a space worthy of tourists. Therefore, the conditions reinforced the idea of creating a tourism village. In this research, location-based discussion was conducted through a fuzzy inference system, Finally, the Fuzzy Topsis method has been used to protect the environment and to some extent extend sustainable tourism development. The ranking of these sites is based on environmental criteria. In the fuzzy inference system by applying the layers required in this method, four sites are considered to be very suitable.Then, using Fuzzy Topsis, which includes 10 criteria and 4 options, identified the best site on site 4. This site will bring the least damage to the environment, Located on the banks of the Dez River, most of the area has been covered by ground. In terms of maintaining environmental criteria, the site has a completely organic environment than other sites.

---

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.

---