Purpose: Full employment has a mysterious meaning, full employment certainly does not mean employment of any member of the active population of the society who is of working age.one reason is that there are probably always people who find themselves unemployed due to various disabilities. Another reason is that at any time you can find workers who want to change jobs and remain unemployed during the job change period. Methodology: The method of descriptive correlation research was used and in terms of purpose, type of research It is applied and the library method is used to complete the literature and research background and the field data is collected through the archives and documents of the Central Bank website and the data of the Stock Exchange and Securities Organization to facilitate the analysis of data from Excel spreadsheet and regression method and Eviews statistical software are used to test research. Findings: The results show that the effect of stock index on variable risk and software use and comprehensive statistics of our research includes all banks and credit institutions listed on the stock exchange. Originality/Value: The available statistics show that the developed stock exchanges are located in developed countries and in these countries, more than anything, investment security is provided for the entry of domestic and foreign investors in the stock exchange. Market security is affected by various factors such as political, economic, and social and others. But in this study we intend to analyze macroeconomic variables.

In this paper a mathematical model for the green supply chain network problem is designed. In this research, we seek to optimize two inconsistent and conflicting goals of the problem which are as follows: 1.Minimization of costs 2.Minimization of environmental impacts, using of the economic indicator 99 method. Methodology: In this paper, two methods of Epsilon constraint and NSGA II algorithm are used to solve the two-objective model with the objective functions of minimizing network costs and minimizing emissions. Findings: The results show that the introduced NSGA II algorithm has a high efficiency in forming efficient solutions in a short time. Originality/Value: In this paper, a two-objective model for green supply chain network is modeled and solved with the aim of reducing network costs and reducing greenhouse gas emissions.