Although the importance of locating in manufacturing and service companies is not a new issue, one of significance applications is to determine the appropriate location for warehouses in manufacturing workshops warehouses to the maintenance of materials or products. In any organizations, Finding the suitable site for warehouses establishments to increase customer service and efficiency is one of the most important and costly issues. The warehouse location is the main decision and structurally multi-criteria that includes quantitative and qualitative objectives. In this study, we apply an MADM technique to achieve the primary ranking for the proposed and potential warehouse locations of the company, and then put them as the input of the UTAStar, which is a new and more practical to inference utility functions from past decision data. We will investigate the utility of the results and define the desirability of ranked options for evaluating and selecting of warehouse space.

Supplier selection is a multi-criterion issue which embraces both qualitative and quantitative criteria. In order to select the best suppliers, it is necessary to make a trade-off between these criteria, yet some of them may conflict. In this article, we present a decision aide supporting system so that first of all suppliers are evaluated and ranked by utilizing TOPSIS method and then the marginal utility function of the problem are estimated by UTASTAR method. In the end, we can evaluate other suppliers of the organization or suppliers which the organization wants to work with in future.

Nowadays supply chain sustainability efforts are continuing to grow globally.  While the focus of typical supply chain management mostly is on the speed, cost and reliability of operations, sustainable supply chain management adds the goals of upholding environmental, financial and social responsibilities. Although the worth of supply chain management in large-scale projects, in particular, the construction industry has been recognized currently, its execution remains subject to significant challenges. One of the main challenges is the complexity of the sustainable suppliers’ selection. They can enhance the profitability and success of the project-oriented construction organizations. In this respect, this article aims to apply fuzzy Utilities-Additives STAR (UTASTAR), the extended Utilities Additives Method for multiple criteria decision, to select sustainable suppliers and evaluate general utility function of the problem. Finally, since this method belongs to compensatory multi-criteria decision-making models the results obtained through the application of the fuzzy UTASTAR were compared with some selected models from the compensatory subgroup. According to comparative results, fuzzy UTASTAR can identify deviation from actual utility of alternatives using upper and lower estimations. As a result, this study shows that the rankings produced by the fuzzy UTASTAR method are more trustworthy for selecting suppliers in ensuring the sustainable development.

Financial decision-making is a principal part of any decisions; hence, great efforts are made to improve the methods to assess and analyze the stocks in financial markets as an important part of the financial decisions. This paper addresses the stock selection by discovering the investor's utility function. Investors in the Stock Exchange consider diverse criteria to buy securities and bonds. Due to the criteria development in stock selection, understanding the investor's behavior by a consultant is a prominent issue. Recognizing an exclusive utility function, according to the characteristics of the investors, facilitates acquiring each share's value for the decision-maker (DM). In this study, UTASTAR method is used to estimate the marginal value function by using 3 appropriate criteria (risk, return, and liquidity) and, finally, fit the total utility function. It provides an opportunity to make a rational decision adjustable to the investor's mentality that considers their ranking, prioritization, selection, or classification. The ranking of the options is as compatible as possible to the original one. The method is applied to an example from Iran Stock Exchange.