Evaluate Relationship between Index of Labor Productivity and Wages in the Big Industrial Workhouse, based on Metaheuristic algorithms and Bayesian Networks

In order to grow and improve productivity of organization, it is necessary to identify effective factors and then, based on their importance, appropriate actions to be taken. The aim of this study is determine the factors that directly and indirectly effect on the productivity of labor and wages, simultaneously, and also examine how these two indicators effect on each other. In this context, due to the ability of the bayesian networks to meet the objectives of this research and, metaheuristic algorithm to achieve maximum efficiency while minimal processing, we will discover and evaluate of casual relationships between internal variables (specifically, wages and labor productivity) of Industrial workhouse with 10 and more than 10 employees in 1386, as the latest data available, that include 13239 firms.
The results of the final version of the model that has been tested through a variety of bayesian networks, show that in addition to the wages of employees is a function of value added, productivity is also a function of added value and wages. Effect of value added on labor productivity is about 4 times higher than the impact of the wages of employees on it.