پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 158 |
| تعداد شماره‌ها | 6,225 |
| تعداد مقالات | 67,685 |
| تعداد مشاهده مقاله | 114,981,431 |
| تعداد دریافت فایل اصل مقاله | 89,653,513 |
ارائۀ مدلی برای طراحی زنجیرۀ تأمین فراورده‌های خونی در زمان وقوع بحران زلزله با در نظر گرفتن انتقال از سایر استان‌ها (مطالعۀ موردی: شبکۀ انتقال خون تهران) | ||
| مدیریت صنعتی | ||
| مقاله 9، دوره 8، شماره 3، آبان 1395، صفحه 487-513 اصل مقاله (926.29 K) | ||
| نوع مقاله: مقاله علمی پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22059/imj.2016.61717 | ||
| نویسندگان | ||
| جمال نهفتی کهنه1؛ ابراهیم تیموری* 2 | ||
| 1کارشناس ارشد مهندسی صنایع، دانشکدۀ مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران | ||
| 2دانشیار دانشکدۀ مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران | ||
| چکیده | ||
| از دیرباز تا کنون انسان‌ها در موارد مختلفی از قبیل خونریزی‌های شدید، پیوند اعضا و غیره، به فراورده‌های خونی نیاز داشته‌اند. یکی از موقعیتهایی که نیاز به فراورده‌های‌خونی به‌شدت افزایش مییابد و شبکۀ انتقال خون در تأمین آن دچار مشکل می‌شود، هنگام وقوع بحرانی مانند زلزله است. در این مقاله با طراحی زنجیرۀ تأمین فراورده‌های خونی مطابق با دنیای واقعی، سعی بر پاسخگویی به نیاز متقاضیان این فراورده‌ها در زمان وقوع بحران زلزله شده و به‌دلیل ناتوانی شهر حادثه‌دیده در زمان وقوع این بحران در تأمین فراورده‌های خونی مورد نیاز خود، بحث انتقال این فراورده‌ها از مراکز استان‌های مجاور مطرح شده است. این مسئله به‌صورت دوهدفه تحت عدم قطعیت فازی مدل‌سازی شده و از روش محدودیت اپسیلون اصلاحی برای حل آن استفاده شده است. مطالعۀ موردی در خصوص وقوع بحران زلزله در شهر تهران با استفاده از اطلاعات شبکۀ انتقال خون این شهر بررسی شده است. نتایج نشان می‌دهد با درنظرگرفتن امکان انتقال فراورده‌های خونی از سایر استان‌ها، می‌توان به تصمیم‌گیرندگان امر شبکۀ انتقال خون برای افزایش خدمت‌رسانی به متقاضیان در زمان زلزله کمک شایانی کرد. | ||
| کلیدواژه‌ها | ||
| زنجیره تامین فرآورده‌های خونی؛ برنامه‌ریزی ریاضی فازی؛ روش محدودیت اپسیلون اصلاحی؛ بحران زلزله؛ شبکه انتقال خون تهران | ||
| عنوان مقاله [English] | ||
| A model for the design of blood products supply chain at the time of the earthquake disaster considering the transfer from the other provinces (Case Study: Tehran blood transfusion network) | ||
| نویسندگان [English] | ||
| Jamal Nahofti Kohneh1؛ Ebrahim Teimoury2 | ||
| 1School of Industrial Engineering, Iran University of science & Technology | ||
| 2Associate Prof. of Industrial Engineering, Iran University of Science & Technology, Tehran, Iran | ||
| چکیده [English] | ||
| Up to now, blood products in various conditions such as severe bleeding, organ transplants were essential for human. One of the situations that leads to increase in needs of blood products highly and blood transfusion network is faced with problem to supply of them, when a disaster for example an earthquake happens. In this paper, for approaching to the real world, a mathematical model for designing of blood products supply chain in disaster time is proposed and due to inability of affected city to supply of needed blood products, the issue of transferring of these products from adjacent provinces has considered. The model is bi-objective and the corrected constraint method is used to solve it. The case study about the earthquake disaster in Tehran has studied using the data of blood transfusion network. The results show considering the possibility of blood products transfusion from other provinces can help to decision makers in order to increase the service to applicants of blood products in disaster time. | ||
| کلیدواژه‌ها [English] | ||
| Blood products supply chain, Fuzzy mathematical programming, Corrected constraint method, Earthquake disaster, Tehran blood transfusion network | ||
| مراجع | ||
|
American Association of Blood banks. (2008). Disaster operations handbook-Hospital. Chapter 3, AABB Pub. Co., New York.
Arvan, M., Tavakkoli-Moghaddam, R., & Abdollahi, M. (2015). Designing a bi-objective and multi-product supply chain network for the supply of blood. Uncertain Supply Chain Management, 3(1), 57-68.
Babazadeh, R., Razmi, J., Pishvaee, M.S., & Rabbani, M. (2016). A sustainable second-generation biodiesel supply chain network design problem under risk. Omega, Accepted Manuscript.
Beliën, J. & Forcé H. (2012). Supply chain management of blood products: A literature review. European Journal of Operational Research, 217(1), 1-16.
Cetin, E. & Sarul, L. S. (2009). A blood bank location model: A multi objective approach. European Journal of Pure and Applied Mathematics, 2(1), 112-124.
Green, G.B., Modi. S., Lunney, K. & Thomas, TL. (2003). Generic evaluation methods for disaster drills in developing countries. Annals of emergency medicine, 41(5), 689-699.
Gunpinar S. & Centeno, G. (2014). Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals. Computers & Operations Research, 54, 129-141.
Hemmelmayr, V., Doerner, K. F., Hartl, R. F. & Savelsbergh M. W. (2010). Vendor managed inventory for environments with stochastic product usage. European Journal of Operational Research, 202(3), 686-695.
Hemmelmayr, V., Doerner, K. F., Hartl, R. F. & Savelsbergh M. W. (2010). Delivery strategies for blood products supplies. OR spectrum, 31(4), 707-725.
Hosseinzadeh, M., Menhaj, M.B. & Kazemi, A. (2015). A method for solving possibilistic multi-objective linear programming problems with fuzzy decision variables. Journal of Industrial Management, 6(4), 709-724. (in Persian) Iranian Blood Transfusion Organization. (2015). http://www.ibto.ir/.
Jabbarzadeh, A., Fahimnia, B. & Seuring, S. (2014). Dynamic supply chain network design for the supply of blood in disasters: A robust model with real world application. Transportation Research Part E: Logistics and Transportation Review, 70: 225-244.
Jacobs, D. A, Silan, M. N & Clemson, B. A. (1996). An analysis of alternative locations and service areas of American Red Cross blood facilities. Interfaces, 26(3), 40-50.
JICA, C. (2000). The study on seismic microzoning of the Greater Tehran Area in the Islamic Republic of Iran. Pacific Consultants International Report, OYO Cooperation, Japan.
Jiménez, M., Arenas, M. & Bilbao, A. (2007). Linear programming with fuzzy parameters: an interactive method resolution. European Journal of Operational Research, 177(3), 1599-1609.
Khorshid, S. & Mahfouzi Mousavi, J. (2010). Measuring and analyzing model of manufacturing organizations need to be agile by using MADM techniques and fuzzy approach. Journal of Industrial Management, 2(4), 37-56. (in Persian) Lashkar Ara, A., Kazemi, A., Gahramani, S. & Behshad, M. (2012). Optimal reactive power flow using multi-objective mathematical programming. Scientia Iranica, 19(6), 1829–1836.
Mahmoodian Shooshtari, M., Pourfathollah, A. (2006). An overview analysis of blood donation in the Islamic Republic of Iran. Archives of Iranian Medicine. 9 (3), 200–203.
Mohamadi, A., Yaghoubi, S., Nahofti Kohneh, J. & Pishvaee, M. S. (2015). Locating shelters and telecom-relief centers considering uncertainty in the disaster time (Case study: flood disaster in region #3 of Tehran), Journal of Industrial Management, 7(1), 125-149. (in Persian)
Mostafa, M. M., Sheaff, R., Morris, M. & Ingham V. (2004). Strategic preparation for crisis management in hospitals: empirical evidence from Egypt. Disaster Prevention and Management: An International Journal, 13(5), 399-408.
Motamedi, N., Shirazi, M. M. & Nouraei, N. (2012). Designing a Rescue System for Earthquake-Stricken Area with the Aim of Facilitation and Accelerating Accessibilities (Case Study: City of Tehran). Proceedings of World Academy of Science, Engineering and Technology, World Academy of Science, Engineering and Technology, 69: 380-383.
Nagurney, A. Masoumi, A. H. & Yu, M. (2012) Supply chain network operations management of a blood banking system with cost and risk minimization. Computational Management Science, 9(2), 205-231.
Nahmias, S. (1982) Perishable inventory theory: A review. Operations research, 30(4), 680-708.
Nateghi, A. F. (2001). Earthquake scenario for the mega-city of Tehran. Disaster Prevention and Management, 10(2), 95-100.
Osorio, A. F., Brailsford, S. C. & Smith, H. K. (2015). A structured review of quantitative models in the blood supply chain: a taxonomic framework for decision-making. International Journal of Production Research, 53(24), 7191-7212.
Pelling, M., Maskrey, A., Ruiz, P., Hall, L. (2004). A Global Report: Reducing Disaster Risk a Challenge for Development. United Nations Development Programme, Bureau for Crisis Prevention and Recovery.
Pierskalla, W.P. (2004). A Handbook of Methods and Applications. Chapter 5: Supply chain management of blood banks. Operations Research and Health Care., Kluwer’s International Series, Dordrecht.
Pishvaee, M. S., Rabbani, M., & Torabi, S. A. (2011). A robust optimization approach to closed-loop supply chain network design under uncertainty. Applied Mathematical Modelling, 35(2), 637-649.
Şahin, G., Süral, H., & Meral, S. (2007). Locational analysis for regionalization of Turkish Red Crescent blood services. Computers & Operations Research, 34(3), 692-704.
Sha, Y. & Huang, J. (2012). The multi-period location-allocation problem of engineering emergency blood supply systems. Systems Engineering Procedia, 5: 21-28.
Shahriari, S., Razavi, S. M. Asgharizadeh, E. A. (2013). Fuzzy Data Envelopment Analysis and a New Approach FIEP / AHP for Full Ranking of Decision Making Units: A Case Study of Humanities Faculty of Tehran University, Journal of Industrial Management, 5(1), 21-42. (in Persian)
Tehran navigation system (2015). “http://map.tehran.ir.
Van Zyl, G. J. J. (1964). Inventory control for perishable commodities, PhD dissertation, University of North Carolina.
Verkuilen, J. (2005). Assigning membership in a fuzzy set analysis. Sociological Methods & Research, 33(4), 462-496.
Zangi abadi, A. & Tabrizi, N. (2006). Tehran earthquake and evaluating the space of vulnerability in urban areas. Geographical Research Quarterly, 38(1), 115-130. (in Persian)
Zendehdel, M., Bozorgi-amiri, A. & Omrani, H. A. (2014). Location Model for Blood Donation Camps with Consideration of Disruption. Journal of Industrial Engineering, 48: 33-43. (in Persian) | ||
|
آمار تعداد مشاهده مقاله: 1,198 تعداد دریافت فایل اصل مقاله: 1,529 |
||