نوع مقاله : مقاله پژوهشی
نویسندگان
1 مربی، گروه مدیریت، واحد امیدیه، دانشگاه آزاد اسلامی، امیدیه، ایران. رایانامه: kasra_kk200218@yahoo.com
2 گروه ریاضی، واحد مشهد، دانشگاه آزاد اسلامی، مشهد، ایران. رایانامه: doosti424@gmail.com
چکیده
کلیدواژه‌ها
عنوان مقاله [English]
نویسندگان [English]
In the present paper, the cogeneration program in the form of an inverse supply chain using multi-objective mathematical modeling in conditions of uncertainty is considered. The supply chain process consists of three levels including suppliers, manufacturers and customers, and there is a maintenance center and a reconstruction center. The first objective function of the model is to minimize costs; the second objective is to maximize the quality of the product. In the mentioned supply chain, the third and fourth objective functions represent minimizing the total weight of the maximum shortage among customers and maximizing the total weight of the minimum supply of goods from suppliers. In this model, the third objective function is designed in conditions of uncertainty using the Malloy stabilization method based on scenario writing. It is called MPSOGA.
کلیدواژه‌ها [English]
Ahmadianfar, I & Adib, A,(.1394) Optimization of Hydropower Energy Utilization of Dams Using a Combined Method of Particle Swarm Algorithm and Genetic Algorithm) Case Study: Dez Dam, Irrigation Science and Engineering (Agricultural Scientific Journal), 38(3). (in Persian). DOI: https://doi.org/10.22055/jise.2015.11475
based aggregate production planning with capacity expansion in DOI: https://doi.org/10.1016/j.cie.2011.10.016
chain problem with two objective functions, Master Thesis, Industrial DOI: https://doi.org/10.1007/978-3-540-71805-5_79
Chen,C. L. & and Lee, W. C. (2004). Multi-objective optimization of multi-echelon supply chain networks with uncertain product demands and prices.Computers and Chemical Engineering, 28(6- 7): 1131-1144. DOI: https://doi.org/10.1016/j.compchemeng.2003.09.014
consideration of deferral policy, Quarterly Journal of Industrial DOI: https://doi.org/10.2307/2523170
Hosseini, S, M, H,(1399). Modeling and Integrated Problem Solving Integrated Production Planning and Maintenance in a Two-Purpose Mode with a Customer Dissatisfaction Approach, Scientific- Research Journal, Industrial Management Studies, (56).(in Persian). DOI: https://doi.org/10.1016/j.ejor.2006.06.032
Khatami Firoozabadi, S, M, A & Makoei, A, .(1392) Integrated Production Planning of Iran Pipe and Machinery Company with the Ideal Gray Planning Approach, Management Research Journal of Tomorrow / 12(35). (in Persian). DOI: https://doi.org/10.22059/ijms.2023.324763.674575
Kopaei Haji, K, Rashidi Komijan, A.(1394) Presenting an integrated model of integrated production and procurement planning with a discount system, The second national conference on industrial engineering research. (in Persian). DOI: https://doi.org/10.30495/jiei.2023.1988013.1308
Makoei, A. & Azami. (2016). A robust optimization Model for Multi-Factory Integrated Production Planning of Perishable Products under Uncertainty Conditions Considering Postponement Policy, Quarterly Journal of Industrial Management Studies, 43: 27-51. (in persian) DOI: https://doi.org/10.1057/palgrave.jors.2602159
Management Studies, 43: 27-51. (in Persian) DOI: https://doi.org/10.29252/payesh.20.1.15
manufacturing systemsComputers & Industrial Engineering.62(2): 491–503 DOI: https://doi.org/10.22105/jarie.2021.275841.1265
Masud, A. S. & Hwang, C. L. (1980). An Aggregate Production Planning Model and Application of Three Multiple Objective Decision Methods. International Journal of Production Research,18(6): 741-752. DOI: https://doi.org/10.1080/00207548008919703
Mirzapour ,hashema, , Babolib, A. & Sazvarb, C. ( 2013). A stochastic aggregate production planning model in a green supply chain: Considering flexible lead times, nonlinear purchase and shortage cost functions European, Journal of Operational Research, 23(1): 26–41. (in persian) DOI: https://doi.org/10.1016/j.ejor.2013.03.033
Mirzapour ,hashema, Aryanezhad, & Sadjadi, S. j. (2012). An efficient algorithm to solve a multi- objective robust aggregate production planning in an uncertain environment, The International Journal of Advanced Manufacturing Technolog. 58(5): 765-782. (in persian) DOI: https://doi.org/10.1007/s00170-011-3396-1
Moghaddam, S. & Yousefi, A. & Karbasian, M. & Khayyam, b. B. (1397). A robust optimization model for multi-factory integrated production DOI: https://doi.org/10.24818/18423264/52.4.18.15
Mohammadzadeh, H. & Zare, Y. M.(1393). A robust optimization model of integrated production program in green supply chain under uncertainty conditions for selecting suppliers, manufacturers and distributors, Thesis, Yazd University-Faculty of Industrial Engineering. (in persian) DOI: https://doi.org/10.48550/arXiv.2208.02926
Nam, S. J. & Logendran, R. (1992). Aggregate production planning –a survey of models and methodologies. European Journal of Operation Research,61(3): 255-272. DOI: https://doi.org/10.5267/j.ijiec.2018.6.002
Nazari, L & Rahmani, M. (1398).Integrated robust production planning for risk-averse managers in conditions of uncertainty, Journal of Industrial Engineering Research in Production Systems, Spring and Summer,(14) (in Persian). DOI: https://doi.org/10.1007/978-3-031-47394-4_51
Optimizing reliability and cost of system for aggregateproduction planning in a supply chain, The International Journal of Scientia Iranica E (2017) 24(6), 3394-3408. (in persian) DOI: https://doi.org/10.24200/sci.2017.4398
planning of perishable products under conditions of uncertainty with DOI: https://doi.org/10.1155/2022/1606331
Rabieh, M. (1390). Provide an innovative method to solve a two-tier supply DOI: https://doi.org/10.1007/s10479-022-04713-4
Renqian, Z. & Lankang, Z. & YiYong, X. & Ikou, K. (2012). The activity- DOI: https://doi.org/10.1016/j.cie.2011.10.016
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