Volume 20, Issue 3 (9-2023)                   jor 2023, 20(3): 141-160 | Back to browse issues page


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Farahbakhsh M, Modiri M, Khatami FirozAbadi M, Pourebrahimi A. Providing a Product Life Cycle Optimization Using Agent Based Modeling Simulation. jor 2023; 20 (3) :141-160
URL: http://jamlu.liau.ac.ir/article-1-2128-en.html
Department of Industrial Management, South Tehran Branch, Islamic Azad University, Tehran, Iran
Abstract:   (355 Views)
With increasing competition in global markets, organizations are paying more attention to the life cycle of their products. To achieve this goal, it is necessary to decide on the studies conducted in the product life cycle, 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, consumer, producer, government, capital and technology factors are considered for simulation, with the help of which you try to study the process of electricity generation and build this process according to the amount of consumption and technology, as well as use. Among them is the reduction of carbon dioxide emissions and their effects on the environment. To analyze the results and optimize the model, the Anylogic software was taken, which was implemented after the implementation of the model to optimize the results of the scenario according to the opinions of experts and the final result was obtained. According to the studies performed from the optimization model presented with the actual results in the results between 2011 to 2019 was consistent with a small distance, which indicates a high validity of the model, also to optimize the model to reduce air and reduce Carbon emissions reduced fossil fuel consumption by changing the technology factor, resulting in a significant reduction in air consumption.
Full-Text [PDF 1203 kb]   (140 Downloads)    
Type of Study: Research | Subject: Special
Received: 2022/01/22 | Accepted: 2022/06/17

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.