Identification of Players in the Database of Public and Private Banks with a Meta-Heuristic Algorithm

The research aims to identify players in the database of public and private banks using a meta-heuristic algorithm. This issue pertains to enhancing the human resources management system to ensure consistent stability in the bank's operations. In this database analysis process, Poisson distribution and artificial intelligence are utilized to analyze data with an exponential distribution. For this purpose, the VIS, CNSGA-II, NSGA-II, MISA, NNIA, and NRGA algorithms were implemented using MATLAB software. The VIS algorithm showed the best performance in most criteria. Algorithms CNSGA-II and MISA are both ranked second and exhibit similar performances. NSGA-II algorithm is ranked second. The NNIA algorithm performs the best, while the NRGA algorithm performs the worst. These analyses are conducted to assess the performance of algorithms based on various criteria. The results obtained from these analyses show that the VIS algorithm generally demonstrates the best performance. This means that VIS is known as an identification of players in the databases of public and private banks. In addition to the Variable in Neighborhood Search (VIS) algorithm, other algorithms like CNSGA-II and MISA are also closely ranked and share the second position in various criteria. These algorithms have similar functions and can make comparable enhancements in identifying players in the databases of public and private banks.

Keywords:

A-Player , Job classification , state bank , private bank , Metaheuristic Algorithm