Provide a product life Cycle Optimization Model Using Agent Based Simulation
محورهای موضوعی : International Journal of Finance, Accounting and Economics Studies
mohammad farahbakhsh
1
(
Phd student of industrial management Operation Research / Islamic Azad university Research and technology Branch/ Tehran/Iran
)
mahmod modiri
2
(
Assistant Prof. in Industrial Management, Faculty of Management, Tehran South Branch, Azad Islamic University, Tehran, Iran
)
seyed mohammad ali khatami firozabadi
3
(
Industrial management، Allameh Tabatabai University, Tehran, Iran
)
alireza Puorebrahimi
4
(
Assistant Prof, Department of Industrial Management, Faculty of Management and Accounting, Islamic Azad University, Karaj, Alborz, Iran
)
کلید واژه: Agent Based Modelling Simulation (ABMS), Optimization, Power Industry, product life cycle,
چکیده مقاله :
With increasing competition in global markets, organizations are paying more attention to the life cycle of their products. To achieve this goal, careful decision-making about the variables affecting the product life cycle is necessary, and the more factors are considered, the better the result. Therefore, in this research, an attempt has been made to provide a life cycle optimization model for the electricity industry. In this model the factors of consumer, producer, government, investor and technology direction Simulations have been considered with the help of which we try to study the process of electricity generation and optimize this process according to changes in consumption and technology, as well as reducing the level of carbon dioxide emissions and its effects on the environment. To analyze the results and optimize the model, Anylogic software was used. After implementing the model to optimize the results, a number of scenarios were examined according to the opinions of experts and the final conclusion was reached. According to the studies, the results of the optimization model presented with the actual results available between 1390 to 1398 corresponded to a small distance, which indicates the high validity of the model, also to optimize the model to reduce air pollution and Reducing carbon emissions by changing the technology factor, we saw a reduction in fossil fuel consumption and thus a significant reduction in air pollution.
