کاربرد نظریه بازی در بهینه‌سازی مسئله حمل‌ونقل سبز چندسطحی با ذینفعان چند‌گانه
محورهای موضوعی :
مدیریت صنعتی
mahmood darvishsefat
1
,
Javad Rezaeian
2
,
Mohammad Mahdi Pourpasha
3
1 - Ph.D. Student in Industrial Management, Production and Operations Orientation, Faculty of Management, Islamic Azad University, Firuzkuh Branch, Iran
2 - Industrial Engineering, Mazandaran University of Science and Technology
3 - Assistant Professor, Department of Mathematics, Islamic Azad University, Chalus Branch, Iran
تاریخ دریافت : 1401/04/01
تاریخ پذیرش : 1401/08/10
تاریخ انتشار : 1401/10/01
کلید واژه:
نظریه بازی,
ذینفعان چند گانه,
حمل و نقل سبز چند سطحی,
چکیده مقاله :
تئوری بازی حوزه ای از ریاضیات کاربردی است و به مطالعه رفتار راهبردی یعنی شرایطی که مطلوبیت هرعامل، به انتخاب خود و بازیگران دیگر همبستگی دارد می پردازد. زندگی روزمره ما، مثال هایی بیشمار از چنین وضعیتی دارد. هدف از انجام این تحقیق مدل سازی و حل مسله حمل و نقل سبز چند سطحی و ذینفعان متعدد به کمک تئوری بازی با مطرح کردن سناریو های مختلف به نحوی که کلیه ذینفعان حاضر در بازی به حدکثر منافع خود دست یابند می باشد. لذا یک مدل جامع چند سطحی زنجیره تأمین متشکل از چند ذینفع همزمان، در نظر گرفته شده است، در مرحله اول با توجه به فاکتور های حمل و نقل و توزیع محصول بین اعضای زنجیره، مدل بهینه جهت دستیابی به کمترین هزینه در سطوح مختلف شامل، کمترین هزینه های خرید و تولید، نگهداری، کمبود و انبار همچنین کمینه سازی میزان دی اکسید کربن تولید شده در مراحل مختلف تولید و حمل برای طرفین بدست می آوریم، در ادامه رقابتی در چهار چوب یک بازی جهت انتخاب حالتی بهینه بین ذینفعان زنجیره تامین ارائه خواهد شد تا بهترین تصمیم در شرایط یک بازی مشارکتی با در نظر گرفتن سناریو های مختلف اتخاذ گردد. در این راستا از نرم افزار اکسل و گمز جهت مدل سازی و حل مثال عددی مطرح شده استفاده شد و نتایج بدست آمده برتری مقادیر بهینه مدل تئوری بازی را تایید کرد.
چکیده انگلیسی:
Game theory, a branch of applied mathematics, which has been recently used to study strategic behavior, i.e. the conditions in which the desirability of each factor depends on the decisions made by the players. The paper proposes a multilevel green transportation model under multi-stakeholder’s condition, that game theory could be used to selects the best interactive mode by presenting different scenarios so that all stakeholders in a game achieve their maximum benefits.In this paper, a comprehensive multi-level supply chain model consisting of several simultaneous stakeholders has been considered. An optimal model was developed to achieve the lowest cost at different levels of the chain. The optimal model includes the lowest costs of purchase and production, maintenance, shortage, and warehousing. The model also includes various components of products transportation and distribution for all members of the chain. The produced Co2 at different stages of production and transportation for both involved parties was accounted in the model to minimize the environmental impacts. Furthermore, a competition in the context of a game to select the optimal situation between the stakeholders of the supply chain has been considered make the best decision in terms of a participatory game by considering different scenarios. In this paper, Excel and Gams software were used to model and solve the numerical example. The results confirmed the superiority of the optimal values of the game theory model.
منابع و مأخذ:
Araghi, N. (2017). Optimizing decision-making in the multi-level supply chain with a game theory approach, Business Management PHD Thesis, Faculty of Management and Economics, University of Scientific Research, Tehran. (In Persian)
Asghari, N., Eshaghi Gorji, M. & Abounoori, E. (2019). Modeling budget distribution in Iran using game theory, Quarterly Journal of Modeling of Econometrics, 2,133-153. (In Persian)
Chakraborty, P., & Poddar, M. (2020). Role of Multiple Stakeholders in Value Co-creation and Effects on Medical Tourism. Jindal Journal of Business Research, 9(1), 18-26.
Nur, F. (2020). Developing models and algorithms to design a robust inland waterway transportation network under uncertainty. Mississippi State University.
Gao, J., & You, F. (2019). A stochastic game theoretic framework for decentralized optimization of multi-stakeholder supply chains under uncertainty. Computers & Chemical Engineering, 122, 31-46.
Gholami, M. (2020). A mathematical model for designing supply chain network considering production and transportation planning for production time dependent products, Industrial Management Master Thesis, Ghiasuddin Jamshid Kashani University, Faculty of Industry and Management. (In Persian)
Huang, Y., & Huang, G. Q. (2012). Integrated supplier selection, pricing and inventory decisions in a multi-level supply chain. In Decision-Making for Supply Chain Integration(pp. 47-62). Springer, London.
Jafari-Nodoushan, A., Fakhrzad, M. B., & Maleki, H. (2022). Optimization of the green supply chain management considering uncertainty in consequence of risk (Case Study: Golsam company). Journal of Industrial and Systems Engineering, 14(2), 322-340.
Kannan, D. (2018). Role of multiple stakeholders and the critical success factor theory for the sustainable supplier selection process. International Journal of Production Economics, 195, 391-418.
Lima, C., Relvas, S., & Barbosa-Póvoa, A. P. F. (2016). Downstream oil supply chain management: A critical review and future directions. Computers & Chemical Engineering, 92, 78-92.
Mahmoudi, R. (2019). Designing a sustainable urban transportation network using data envelopment analysis and game theory, Industrial Engineering PHD Thesis, Isfahan University of Technology, Faculty of Industrial and Systems Engineering. (In Persian)
Masheli A. & Mohamaditabar, D. (2017). Selecting suppliers with a collaborative game theory approach considering capacity constraints and sending items simultaneously, Journal of Industrial Engineering Research in Production Systems, no 10. (In Persian)
Salimi, P. & Edalatpanah, SA. (2020). Supplier selection using fuzzy AHP method and D-numbers, Journal of fuzzy Extension and Applications, 1-14. 10. 22105/jfea.2020.248437.1007.
Babu, S., & Mohan, U. (2018). An integrated approach to evaluating sustainability in supply chains using evolutionary game theory. Computers & operations research, 89, 269-283.
Gao, J., & You, F. (2019). A stochastic game theoretic framework for decentralized optimization of multi-stakeholder supply chains under uncertainty. Computers & Chemical Engineering, 122, 31-46.
Liu, Z., Qian, Q., Hu, B., Shang, W. L., Li, L., Zhao, Y., ... & Han, C. (2022). Government regulation to promote coordinated emission reduction among enterprises in the green supply chain based on evolutionary game analysis. Resources, Conservation and Recycling, 182, 106290.
Zimmer, K., Fröhling, M., & Schultmann, F. (2016). Sustainable supplier management–a review of models supporting sustainable supplier selection, monitoring and development. International journal of production research, 54(5), 1412-1442.
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Araghi, N. (2017). Optimizing decision-making in the multi-level supply chain with a game theory approach, Business Management PHD Thesis, Faculty of Management and Economics, University of Scientific Research, Tehran. (In Persian)
Asghari, N., Eshaghi Gorji, M. & Abounoori, E. (2019). Modeling budget distribution in Iran using game theory, Quarterly Journal of Modeling of Econometrics, 2,133-153. (In Persian)
Chakraborty, P., & Poddar, M. (2020). Role of Multiple Stakeholders in Value Co-creation and Effects on Medical Tourism. Jindal Journal of Business Research, 9(1), 18-26.
Nur, F. (2020). Developing models and algorithms to design a robust inland waterway transportation network under uncertainty. Mississippi State University.
Gao, J., & You, F. (2019). A stochastic game theoretic framework for decentralized optimization of multi-stakeholder supply chains under uncertainty. Computers & Chemical Engineering, 122, 31-46.
Gholami, M. (2020). A mathematical model for designing supply chain network considering production and transportation planning for production time dependent products, Industrial Management Master Thesis, Ghiasuddin Jamshid Kashani University, Faculty of Industry and Management. (In Persian)
Huang, Y., & Huang, G. Q. (2012). Integrated supplier selection, pricing and inventory decisions in a multi-level supply chain. In Decision-Making for Supply Chain Integration(pp. 47-62). Springer, London.
Jafari-Nodoushan, A., Fakhrzad, M. B., & Maleki, H. (2022). Optimization of the green supply chain management considering uncertainty in consequence of risk (Case Study: Golsam company). Journal of Industrial and Systems Engineering, 14(2), 322-340.
Kannan, D. (2018). Role of multiple stakeholders and the critical success factor theory for the sustainable supplier selection process. International Journal of Production Economics, 195, 391-418.
Lima, C., Relvas, S., & Barbosa-Póvoa, A. P. F. (2016). Downstream oil supply chain management: A critical review and future directions. Computers & Chemical Engineering, 92, 78-92.
Mahmoudi, R. (2019). Designing a sustainable urban transportation network using data envelopment analysis and game theory, Industrial Engineering PHD Thesis, Isfahan University of Technology, Faculty of Industrial and Systems Engineering. (In Persian)
Masheli A. & Mohamaditabar, D. (2017). Selecting suppliers with a collaborative game theory approach considering capacity constraints and sending items simultaneously, Journal of Industrial Engineering Research in Production Systems, no 10. (In Persian)
Salimi, P. & Edalatpanah, SA. (2020). Supplier selection using fuzzy AHP method and D-numbers, Journal of fuzzy Extension and Applications, 1-14. 10. 22105/jfea.2020.248437.1007.
Babu, S., & Mohan, U. (2018). An integrated approach to evaluating sustainability in supply chains using evolutionary game theory. Computers & operations research, 89, 269-283.
Gao, J., & You, F. (2019). A stochastic game theoretic framework for decentralized optimization of multi-stakeholder supply chains under uncertainty. Computers & Chemical Engineering, 122, 31-46.
Liu, Z., Qian, Q., Hu, B., Shang, W. L., Li, L., Zhao, Y., ... & Han, C. (2022). Government regulation to promote coordinated emission reduction among enterprises in the green supply chain based on evolutionary game analysis. Resources, Conservation and Recycling, 182, 106290.
Zimmer, K., Fröhling, M., & Schultmann, F. (2016). Sustainable supplier management–a review of models supporting sustainable supplier selection, monitoring and development. International journal of production research, 54(5), 1412-1442.
