In recent years, the increased incidence of natural disasters with irreparable damage to people has led to various efforts to reduce its destructive effects and consequences. Hence, humanitarian aid logistics are aimed at preserving life and reducing the suffering of people in crises. Facility location is a strategic issue in humanitarian logistics and has a planning role before the crisis. Finding the right place for establishment of the facilities can help relieve the disaster. This research is also based on the principles of non-operational defense and the design of a multi-objective mathematical model for seeking a suitable location for the facility. In this mathematical model based on four population density indexes, user appropriateness, access to the road and enclosure of the appropriate location for the establishment of a hospital, temporary care centers, shelters and warehouses is selected. The designed model is solved using Lexicographic method and via GAMS software.

In recent decades, provision-chain management has been one of the major concepts. The main reason that attracts attention to the concept is the increase in competition and struggle for the survival. There are different ways to increase the competition in organizations such as increasing productivity by acquiring information technology.
In this paper, we present an integrated model with the balanced score card framework for supplier selection strategy. The proposed model of this paper gathers 161 important factors suggested in the literature and selects the six most important ones using different multi criteria techniques. We also propose a goal programming techniques with some hard constraints and implement the mathematical model for real-world case study of auto industry. The proposed model is solved in four different forms using TOPSIS, VIKOR and the combination of these 2 factors with factor analysis. The preliminary results indicate that a combination of VIKOR and factor analysis presented better results with 9% reduction in costs, 38% increase of quality, and 3.2% increase in acceptability.