Dr. León-Castro, Ernesto

Interval numbers are widely used in many fields to provide information about different scenarios. This paper presents several new uncertain average formulations using the ordered weighted average, prioritized, probabilistic and induced operators. First, the work introduces the uncertain prioritized induced probabilistic ordered weighted average (UPIPOWA) operator that its main applicability is in complex group decision making problems. Also, a wide range of special cases and extensions using quasi-arithmetic means are presented, such is the case of the quasi-arithmetic UPIPOWA (QUPIPOWA) operator. The study analyzes the applicability of this new approach in economic variables, specifically are imports and exports. Particularly, the paper focuses on measuring the imports and exports for Latin America for 2017

This article presents the process to build a regional employability indicator based on the ordered weighted average operator. The objective is to generate an indicator that can include different weighting vectors to analyze the information based on an analysis made from States to Regions to Nation. The main advantage of doing this type of indicators is that it is possible to made different politics for each State/Region instead of just analyze the whole Nation information. Also, based on the reordering step of the OWA operator is possible to obtain the maximum and minimum results. An example based on the National Occupation and Employment Survey (ENOE) 2020 survey conducted by the National Institute of Statistics and Geography (INEGI) in Mexico was done. Among the main results is possible to visualize the main characteristics of each Region.

Agricultural products have experienced sudden changes in prices in recent years as a result of volumes of production and demand at the international level. Volatility is a key element in understanding the difficulties that the market may have. However, the traditional formula for volatility only considers historical information and does not consider decision makers’ knowledge and skills. To improve this approach and obtain more accurate results consistent with the reality of the market, the ordered weighted averaging (OWA) operator is used. These new approaches are the OWA-Volatility, Induced OWA-Volatility, Heavy OWA-Volatility, Probabilistic OWA-Volatility, Induced Probabilistic OWA-Volatility and Induced Heavy OWA-Volatility. In addition, some particular cases are presented in which the aggregation process is only applied to one part of the formula or quasi-arithmetic means are used. An example of volatility calculations for corn prices in 2017 is presented.

The main purpose is to propose a new method for approximating the average interest rate using an ordered weighted average. The ordered weighted average (OWA), generalized GOWA operator and interval numbers are studied to develop this method. Using average interest rate formulation combined with aggregations operators and interval numbers presented above is the proposed weighted average interest rate (OWAIR) operator. For mathematical application, the deposit interest rates of the countries with 2020 data on the World Bank website are carried out. Finally, it should be noted that changes in the maximum, minimum, and average values are considered in the use of training for each region, which can be helpful for investors’ decision-making.