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مدل برنامهریزی امکانی چندهدفه برای مسئله طراحی شبکه زنجیره تأمین پلاکت با درنظرگیری عدم قطعیت در تقاضا و تعداد اهداکنندگان | ||
| مدیریت زنجیره تأمین | ||
| دوره 26، شماره 85، اسفند 1403، صفحه 69-87 | ||
| نوع مقاله: پژوهشی | ||
| نویسندگان | ||
| مرضیه مظفری* 1؛ سودابه سبحانی منش2 | ||
| 1گروه مهندسی صنایع، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران | ||
| 2دانش آموخته کارشناسی ارشد گروه مهندسی صنایع، واحد تهران جنوب، دانشگاه آزاد اسلامی، تهران، ایران | ||
| تاریخ دریافت: 12 آذر 1403، تاریخ بازنگری: 23 دی 1403، تاریخ پذیرش: 23 بهمن 1403 | ||
| چکیده | ||
| در سال‌های اخیر به دلایل گوناگونی نظیر شیوع بیماری‌هایی چون سرطان، تصادفات رانندگی، رخداد بلایای طبیعی و ... نیاز به خون و فرآوردههای آن افزایش یافته است. موضوع بسیار مهم در مورد خون و فرآوردههای خونی، فسادپذیری آن‌ها است. جمعآوری بیش‌ازحد خون باعث اتلاف شده، درحالی‌که موجودی ناکافی آن نیز منجر به کمبود و کاهش سطح خدمت در نقاط تقاضا می‌گردد که می‌تواند هزینههای جبران‌ناپذیری را در پی داشته باشد. با توجه به اینکه در دنیای واقعی عرضه خون از سوی اهداکنندگان دارای حالت منظم و مستمر نیست و تقاضا نیز برای فراورده‌های خونی حالت قطعی ندارد، برنامهریزی مناسب جهت جمعآوری و تولید خون و فرآوردههای آن مورد توجه بسیاری از محققان قرار گرفته است. در بین فرآوردههای خونی، پلاکت‌ها با داشتن طول عمری معادل پنج روز فسادپذیرترین فرآورده خونی می‌باشند. لذا در این مقاله به ارائه یک مدل برنامهریزی امکانی چنددوره‌ای تحت شرایط عدم قطعیت در عرضه و تقاضا برای مسئله طراحی یکپارچه شبکه جمعآوری و تولید پلاکت در زنجیره تامین خون پرداخته شده که هدف آن مینیمم کردن هزینههای کل شبکه و ماکزیمم کردن کیفیت پلاکت‌های تولید شده است. مدل پیشنهادی، ویژگی‌های خاص این زنجیره شامل کیفیت پلاکت موردنیاز بیمار، انواع اهداکنندگان و دو روش متفاوت تولید پلاکت (خون کامل و آفرزیس) را در نظر می‌گیرد. پس از تبدیل مدل برنامهریزی امکانی به یک مدل برنامهریزی خطی عدد صحیح مختلط (MILP)، مدل به صورت دقیق با استفاده از CPLEX در نرمافزار GAMS حل شده و کارایی آن با مطالعه موردی شبکه تأمین خون شهر تهران نمایش داده شده است. | ||
| کلیدواژه‌ها | ||
| زنجیره تأمین پلاکت؛ مسئله مکان‌یابی-تخصیص؛ برنامهریزی تولید و موجودی؛ رویکرد برنامهریزی امکانی دوهدفه؛ کیفیت | ||
| عنوان مقاله [English] | ||
| A Multi-Objective Possibilistic Model to Platelet Supply Chain Network Design Considering Uncertainty in Demand and Number of Donors | ||
| نویسندگان [English] | ||
| Marzieh Mozafari1؛ Soudabeh Sobhani-Manesh2 | ||
| 1Department of Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran | ||
| 2Master's degree in Industrial Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran | ||
| چکیده [English] | ||
| In recent years, the need for blood and its products has increased due to various reasons including traffic accidents, natural disasters, spread of diseases such as cancer, etc. A very important issue regarding blood and blood products is their perishability. Excessive blood collection causes waste, while insufficient blood supply leads to shortages at demand points, which can result in irreparable costs. Given that the supply of blood from donors is not regular and continuous and the demand for blood products is not certain in the real world, appropriate planning for the collection and production of blood and its products has attracted the attention of many researchers. Among blood products, platelets are the most perishable blood product, with a lifespan of five days. In this paper, a mixed linear programming (MILP) model under supply and demand uncertainty is presented for the integrated design problem of platelet collection and production network in blood supply chain, which aims to minimize the total network costs and maximize the quality of platelets produced. The specific characteristics of this blood product, such as types of donors and two different platelet production methods (whole blood and apheresis), are considered. In order to solve the model using a probabilistic programming approach, the initial non-deterministic model is converted into a deterministic model and the model is solved exactly by the CPLEX solver in GAMS. The efficiency of the model is demonstrated with a case study related to the blood network of Tehran. | ||
| کلیدواژه‌ها [English] | ||
| Platelet Supply Chain, Location-Allocation Problem, Production and Inventory Planning, Multi-Objective Possibilistic Programming, Quality | ||
| مراجع | ||
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[1] M. S. Pishvaee, J. Razmi, and S. A. Torabi, "Robust possibilistic programming for socially responsible supply chain network design: A new approach," Fuzzy Sets and Systems, vol. 206, pp. 1-20, 2012. https://doi.org/10.1016/j.fss.2012.04.010 [2] G. Van Zyl, "Inventory control for perishable commodities," Ph.D. dissertation, University of North Carolina at Chapel Hill, 1960. [3] S. Nahmias, "Perishable inventory theory: A review," Operations Research, pp. 680-708, 1982. https://doi.org/10.1287/opre.30.4.680 [4] G. Prastacos, "Blood inventory management: an overview of theory and practice," Management Science, pp. 777-800, 1984. https://doi.org/10.1287/mnsc.30.7.777 [5] J. Beliën and H. Forcé, "Supply chain management of blood products: A literature review," European Journal of Operational Research, vol. 217, no. 1, pp. 1-16, 2012. https://doi.org/10.2139/ssrn.1974803 [6] A. F. Osorio, S. C. Brailsford, and H. K. Smith, "A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making," International Journal of Production Research, vol. 53, no. 24, pp. 7191-7212, 2015. https://doi.org/10.1080/00207543.2015.1005766 [7] I. Or and W. P. Pierskalla, "A transportation location-allocation model for regional blood banking," AIIE Transactions, vol. 11, no. 2, pp. 86-95, 1979. https://doi.org/10.1080/05695557908974447 [8] M. S. Daskin, C. R. Coullard, and Z. J. M. Shen, "An inventory-location model: Formulation, solution algorithm and computational results," Annals of Operations Research, vol. 110, pp. 83-106, 2002. https://doi.org/10.1007/978-3-642-02568-6_33 [9] G. Şahin, H. Süral, and S. Meral, "Locational analysis for regionalization of Turkish Red Crescent blood services," Computers & Operations Research, vol. 34, no. 3, pp. 692-704, 2007. https://doi.org/10.1016/j.cor.2005.03.020 [10] E. Cetin and L. S. Sarul, "A blood bank location model: A multiobjective approach," European Journal of Pure and Applied Mathematics, vol. 2, no. 1, pp. 112-124, 2009. [11] M. Arvan, R. Tavakkoli-Moghaddam, and M. Abdollahi, "Designing a bi-objective and multi-product supply chain network for the supply of blood," Uncertain Supply Chain Management, vol. 3, no. 1, pp. 57-68, 2015. https://doi.org/10.5267/j.uscm.2014.8.004 [12] P. Ghasemi, M. Ebrahimi, M. Norouzzadeh, and A. Gheibi, "Multi-objective location and allocation in the blood supply chain: Case study: Mazandaran province," Supply Chain Management, vol. 18, no. 53, pp. 56-68, 2016 (In Persian). [13] E. Teymoury and M.S. Pishvaee, "Blood products supply chain design considering disaster circumstances (Case study: earthquake disaster in Tehran)," Supply Chain Management, vol. 17, no. 50, pp. 6-21, 2016 (In Persian). [14] M. Paydar and M. Habibi-Kouchaksaraei, "Designing a bi-objective multi-echelon robust blood supply chain in a disaster," Supply Chain Management, vol. 17, no. 50, pp. 82-95, 2016 (In Persian). [15] N. Gilani and S. Yaghoubi, "A robust mathematical model for platelet supply chain considering social announcements and blood extraction technologies," Computers & Industrial Engineering, vol. 137, 2019. https://doi.org/10.1016/j.cie.2019.106014 [16] M. Eskandari-Khanghahi, R. Tavakkoli-Moghaddam, A. Taleizadeh, and S. Hassanzadeh, "Designing and optimizing a sustainable supply chain network for a blood platelet bank under uncertainty," Engineering Applications of Artificial Intelligence, vol. 71, pp. 236-250, 2018. https://doi.org/10.1016/j.engappai.2018.03.004 [17] S. Yaghoubi, S.M Hosseini-Motlagh, S. Cheraghi, and N. Gilani Larimi, "Designing a robust demand-differentiated platelet supply chain network under disruption and uncertainty," Journal of Ambient Intelligence and Humanized Computing, vol. 11, pp. 3231–3258, 2020. https://doi.org/10.1007/s12652-019-01501-0 [18] S.M Hosseini-Motlagh, M.R Gatreh Samani, and SH Homaei, "Blood supply chain management: robust optimization, disruption risk, and blood group compatibility (a real-life case)," Journal of Ambient Intelligence and Humanized Computing”, vol. 11, pp. 1085–1104, 2020 https://doi.org/10.1007/s12652-019-01315-0 [19] S. M. Hosseini-Motlagh and M. Ghatreh Samani, "Robust and stable flexible blood supply chain network design under motivational initiatives," Socio-Economic Planning Sciences, vol. 70, 2020. https://doi.org/10.1016/j.seps.2019.07.001 [20] F. Rashidian, "Presenting a Bi-objective Integrated Model of Blood Supply Chain Network Design with the Approach of Increasing the Quality of Products," Industrial Innovations: Requirements and Strategies, vol. 1, no. 3, pp. 255-270, 2023. https://doi.org/10.61186/jii.1.3.255 [21] B. Zahiri and M. S. Pishvaee, "Blood supply chain network design considering blood group compatibility under uncertainty," International Journal of Production Research, vol. 55, no. 7, pp. 2013-2033, 2017. https://doi.org/10.1080/00207543.2016.1262563 [22] M. Zendehdel, A. Bozorgi-Amiri, and H. Omrani, "A location Model for Blood Donation Camps with Consideration of Disruption," Special Issue, vol. 48, pp. 33-43, 2014 (In Persian). [23] S. Cheraghi, S. M. Hosseini-Motlagh, and M. Ghatreh Samani, "Integrated planning for blood platelet production: a robust optimization approach," Journal of Industrial and Systems Engineering, vol. 10, pp. 55-80, 2017. [24] R. Ramezanian and Z. Behboodi, "Blood supply chain network design under uncertainties in supply and demand considering social aspects," Transportation Research Part E: Logistics and Transportation Review, vol. 104, pp. 69-82, 2017. https://doi.org/10.1016/j.tre.2017.06.004 [25] B. Fahimnia, A. Jabbarzadeh, A. Ghavamifar, and M. Bell, "Supply chain design for efficient and effective blood supply in disasters," International Journal of Production Economics, vol. 183, Part C, pp. 700-709, 2017. https://doi.org/10.1016/j.ijpe.2015.11.007 [26] M. Habibi-Kouchaksaraei, M. Paydar, and E. Asadi-Gangraj, "Designing a bi-objective multi-echelon robust blood supply chain in a disaster," Applied Mathematical Modelling, vol. 55, pp. 583-599, 2018. https://doi.org/10.1016/j.apm.2017.11.004 [27] N. Haghjoo, R. Tavakkoli-Moghaddam, H. Shahmoradi-Moghadam, and Y. Rahimi, "Reliable blood supply chain network design with facility disruption: A real-world application," Engineering Applications of Artificial Intelligence, vol. 90, 2020. https://doi.org/10.1016/j.engappai.2020.103493 [28] Y. Xu and J. Szmerekovsky, "A multi-product multi-period stochastic model for a blood supply chain considering blood substitution and demand uncertainty," Health Care Management Science, vol. 25, no. 3, pp. 441-459, 2022. https://doi.org/10.1007/s10729-022-09593-5 [29] H. Shih, A. Kasaie, and S. Rajendran, "A multiple criteria decision-making model for minimizing platelet shortage and outdating in blood supply chains under demand uncertainty," Healthcare Analytics, vol. 3, p. 100180, 2023. https://doi.org/10.1016/j.health.2023.100180 [30] Tsz Yu Suen, X. Song, and D. Jones, "A two-stage stochastic model for a multi-objective blood platelet supply chain network design problem incorporating frozen platelets," Computers & Industrial Engineering, vol. 185, p. 109651, 2023. https://doi.org/10.1016/j.cie.2023.109651 [31] M. R. G. Samani and S. M. Hosseini-Motlagh, "Collaborative activities for matching supply and demand in the platelet network," Expert Systems with Applications, vol. 231, p. 120629, 2023. https://doi.org/10.1016/j.eswa.2023.120629 [32] O. A. Ejohwomu, J. Too, and D. J. Edwards, "A resilient approach to modelling the supply and demand of platelets in the United Kingdom blood supply chain," International Journal of Management Science and Engineering Management, vol. 16, no. 2, pp. 143-150, 2021. https://doi.org/10.1080/17509653.2021.1892548 [33] Sh. Rekabi, H. Shokri Garjan, F. Goodarzian, D. Pamucar, and A. Kumar, “Designing a responsive-sustainable-resilient blood supply chain network considering congestion by linear regression method,” Expert systems with applications, vol. 245, pp. 122976–122976, Jul. 2024, https://doi.org/10.1016/j.eswa.2023.122976. [34] S. Entezari, O. Abdolazimi, M. B. Fakhrzad, D. Shishebori, and J. Ma, “A Bi-objective stochastic blood type supply chain configuration and optimization considering time-dependent routing in post-disaster relief logistics,” Computers & Industrial Engineering, vol. 188, pp. 109899–109899, Jan. 2024, https://doi.org/10.1016/j.cie.2024.109899. [35] S. A. Torabi and E. Hassini, "An interactive possibilistic programming approach for multiple objective supply chain master planning," Fuzzy Sets and Systems, vol. 159, no. 2, pp. 193-214, 2008. https://doi.org/10.1016/j.fss.2007.08.010 | ||
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آمار تعداد مشاهده مقاله: 54 |
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