ارائه مدل استوار دوهدفه برای طراحی یکپارچه شبکه زنجیره تامین خون تحت شرایط عدم قطعیت تقاضا و امکان ارسال جانبی بین تسهیلات

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانش‌آموخته کارشناسی ارشد، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

2 دانشیار، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

3 دانشجوی دکتری، دانشکده مهندسی صنایع، دانشگاه علم و صنعت ایران، تهران، ایران

چکیده

نیاز مبرم و بی­پایان به خون انسان­ها به صورت کافی و ایمن از یک طرف و هزینه­های گزاف سیستم­های سلامت از طرفی دیگر، دولت­ها را بر آن داشته تا در جهت بهبود عملکرد سیستم­های سلامت گام بردارند. یکی از کلیدی­ترین بخش­های یک سیستم سلامت زنجیره تامین خون است که سهم قابل توجهی از هزینه­های این سیستم را به خود اختصاص داده است. بنابراین هرگونه پیشرفتی در عملکرد زنجیره تامین خون می­تواند بطور چشمگیری به بهبود کارآیی و صرفه­جویی­ در هزینه­های سیستم­های سلامت بیانجامد. به منظور دستیابی به کارآیی این زنجیره تامین، داشتن برنامه­ریزی مناسب و درخور چالشی است که توجهی بیش از پیش می­طلبد. در این مقاله به ارائه یک مدل دوهدفه برنامه ریزی خطی عدد صحیح مختلط برای طراحی شبکه جمع­آوری، تولید و توزیع خون تحت شرایط عدم قطعیت و طی یک افق برنامه­ریزی چند دوره­ای با لزوم اتخاذ تصمیمات استراتژیک و تاکتیکی پرداخته می­شود. در مسأله مورد بررسی، امکان ارسال خون مابین مراکز منطقه­ای خون نیز در نظر گرفته شده است. به منظور حل مدل دوهدفه از روش محدودیت اپسیلون1 و برای مقابله با عدم قطعیت تقاضا، از رویکرد بهینه سازی استوار سبک2 استفاده شده است. سودمندی مدل ارائه شده و همچنین روش حل مورد استفاده، با انجام تعدادی مثال عددی و در ادامه تحلیل حساسیت­های مربوطه نمایش داده شده است. در خاتمه، مجموع هزینه­های شبکه که ترکیبی از هزینه­های نقض محدودیت (در نظر گرفتن استواری شدنی بودن) و هزینه­های تابع هدف است، بر اساس دو رویکرد استوار و رویکرد قطعی، به­ عنوان مبنای مقایسه جوابهای حاصل از حل مدل ارائه شده تحت مجموعه­ای از واقع­نمایی­ها3 اتخاذ شده است و نتایج حاصل بیانگر برتری و غلبه رویکرد استوار بر رویکرد قطعی است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

A robust bi-objective model for integrated blood supply chain network design considering transshipment between facilities under uncertainty

نویسندگان [English]

  • Sara Cheraghi 1
  • Seyed Mehdi Hoseini Motlagh 2
  • Mohammadreza Ghatreh Samani 3
1 MSc Student, School of industrial engineering, Iran University of science and technology, Tehran, Iran
2 Iran Science and Technology University
3 Phd Student, School of industrial engineering, Iran University of science and technology, Tehran, Iran
چکیده [English]

Possessing a considerable portion of the cost of any health system, blood supply chain is one of the most critical parts of the system. Accordingly, any improvement in the performance of a blood supply chain can result in significantly improved performance as well as cost of the health systems. To have an efficient blood supply chain, appropriate planning is of great significance. This paper puts forward a bi-objective mixed-integer linear programming model for designing blood collection, production, inventory control and distribution under uncertainty with the need for making both strategic and tactical decisions simultaneously over multiple periods of planning. Moreover, blood transshipment between regional blood centers is accounted for in this work. To deal with the proposed bi-objective model, the epsilon-constraint method is devised, and to capture demand uncertainty, a Light robust approach is applied. The usefulness of the concerned model and its solution technique, which is a combination of epsilon-constraint and Light robust methods, is then evaluated via a set of numerical examples, and also, the sensitivity analysis is provided. We close the research while comparing the performance of both deterministic and robust models based on the network total cost, a performance measure including both constraint violation cost (feasibility robustness) and objective functions (optimality robustness) under a specific realization. The results imply that the robust approach strongly outperforms the deterministic one.

کلیدواژه‌ها [English]

  • blood supply chain
  • Healthcare
  • Epsilon-constraint
  • robust optimization
  • Lateral transshipment
Arvan, M., Tavakkoli-Moghaddam, R. and Abdollahi, M. (2015) "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.
Beliën, J. and Forcé, H. (2012) "Supply chain management of blood products: A literature review", European Journal of Operational Research, Vol. 217, No. 1,  pp. 1-16.
Ben-Tal, A. and Nemirovski, A. (2000) "Robust solutions of linear programming problems contaminated with uncertain data", Mathematical Programming, Vol. 83, No. 3, pp. 411-424.
Bertolini F., Rebulla P., Porretti L. and Murphy S. (1992) "Platelet quality after 15-day storage of platelet concentrates prepared from buffy coats and stored in a glucose-free crystalloid medium", Transfusion, Vol. 32, pp.9–16.
Bertsimas, D. and Sim, M. (2004) "The price of robustness", Operations Research, Vol. 52, No. 1, pp.35-53.
Cheraghi, S. and Hosseini-Motlagh, S. M. (2017) "Optimal blood transportation in disaster relief considering facility disruption and route reliability under uncertainty", International Journal of Transportation Engineering, Vol. 4, No. 3, pp.225-254.
Dehghani, M. and Abbasi, B. (2018)"An age-based lateral-transshipment policy for perishable items", International Journal of Production Economics, Vol.198, pp.93-103.
Duan, Q. and Liao, T. W. (2014) "Optimization of blood supply chain with shortened shelf lives and ABO compatibility", International Journal of Production Economics, Vol.153, pp.113-129.
Eskandari-Khanghahi, M., Tavakkoli-Moghaddam, R., Taleizadeh, A. A. and Amin, S. H. (2018) "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.
Fischetti, Matteo and Michele Monaci (2009) "Light robustness", Robust and Online Large-scale Optimization, Springer Berlin Heidelberg, pp.61-84.    
Ghandforoush, P. and Sen, T. K. (2010) "A DSS to manage platelet production supply chain for regional blood centers", Decision Support Systems, Vol. 50, No.1, pp. 32-42.
Habibi-Kouchaksaraei, M., Paydar, M. M. and Asadi-Gangraj, E. (2018) "Designing a bi-objective multi-echelon robust blood supply chain in a disaster", Applied Mathematical Modelling, Vol.55, pp. 583-599.
Jabbarzadeh, A., Fahimnia, B. and 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, Vol.70, pp.225-244.
Jacobs, D. A., Silan, M. N. and Clemson, B. A. (1996) "An analysis of alternative locations and service areas of American Red Cross blood facilities", Interfaces, Vol.26, No.3, pp.40-50.
Kamyabniya, A., Lotfi, M. M., Naderpour, M. and Yih, Y. (2017) "Robust platelet logistics planning in disaster relief operations under uncertainty: A coordinated approach", Information Systems Frontiers, Vol. 20, No. 4, pp.1-24.
Khalilpourazari, S. and Khamseh, A. A. (2017)" Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application", Annals of Operations Research, pp.1-39.
Kohneh, J. N., Teymoury, E. and Pishvaee, M. S. (2016)" Blood products supply chain design considering disaster circumstances (Case study: Earthquake disaster in Tehran)", Journal of Industrial and Systems Engineering, Vol. 9, pp.51-72.
Levin, E., Culibrk,B., Gyöngyössy-Issa, M., Weiss, S., Scammell, K., LeFresne, W., Jenkins, C. and Devine, D. V. (2008) "Implementation of buffy coat platelet component production: comparison to platelet-rich plasma platelet production", Transfusion, Vol. 48, No.11, pp.2331-2337.
Melo, M. T., Nickel, S. and Saldanha-da-Gama, F. (2009) "Facility location and supply chain management–A review", European Journal of Operational Research, Vol.196, No. 2, pp.401-412.
Mousazadeh, M., Torabi, S. A. and Zahiri, B. (2015) "A robust possibilistic programming approach for pharmaceutical supply chain network design", Computers & Chemical Engineering, Vol.82, pp.115-128.
Mavrotas, G. (2009) "Effective implementation of the ε-constraint method in multi-objective mathematical programming problems", Applied Mathematics and Computation, Vol.213, No.2, pp.455-465.
Nagurney, A., Masoumi, A. H. and Yu, M. (2012) "Supply chain network operations management of a blood banking system with cost and risk minimization", Computational Management Science, Vol. 9, No.2, pp. 205-231.
Nahmias, S. (1982) "Perishable inventory theory: A review", Operations research, Vol.30, No. 4, pp. 680-708.
Osorio, A. F., Brailsford, S. C. and 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, Vol.53, No.24, pp.7191-7212.
Paterson, C., Teunter, R. and Glazebrook, K. (2012) "Enhanced lateral transshipments in a multi-location inventory system", European Journal of Operational Research, Vol.221, No. 2, pp. 317-327.
Pierskalla, W. P. (2005) "Supply chain management of blood banks", In Operations Research and Health Care (pp. 103-145). Springer, Boston, MA.
Prastacos, G. P. (1984) "Blood inventory management: an overview of theory and practice", Management Science, Vol. 30, No.7, pp. 777-800.
Ramezanian, R. and Behboodi, Z. (2017) "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.
Riahi, N., Hosseini-Motlagh, S. M. and Teimourpour, B. A. (2013) Three-phase hybrid times series modelling framework for improved hospital inventory demand forecast, International Journal of Hospital Research, Vol. 2, No. 3, pp. 133142.
Şahin, G., Süral, H. and Meral, S. (2007) "Locational analysis for regionalization of Turkish Red Crescent blood services", Computers & Operations Research, Vol.34, No.3, pp.692-704.
Salehi, F., Mahootchi, M. and Husseini, S. M. M. (2017)" Developing a robust stochastic model for designing a blood supply chain network in a crisis: A possible earthquake in Tehran", Annals of Operations Research, pp.1-25.
Samani, M. R. G., Torabi, S. A. and Hosseini-Motlagh, S. M. (2018) "Integrated blood supply chain planning for disaster relief".,International Journal of Disaster Risk Reduction, Vol. 27, pp.168-188.
Schreiber, G. B., Schlumpf, K. S., Glynn, S. A., Wright, D. J., Tu, Y., King, M. R., ... and Guiltinan, A. M. (2006) "Convenience, the bane of our existence, and other barriers to donating", Transfusion, Vol. 46, No.4, pp. 545-553.
Sha, Y. and Huang, J. (2012) "The multi-period location-allocation problem of engineering emergency blood supply systems", Systems Engineering Procedia, Vol. 5, pp.21-28.
Singh, C. (1982) "Convex programming with set-inclusive constraints and its applications to generalized linear and fractional programming", Journal of Optimization Theory and Applications, Vol.38, No.1, pp.33-42.
Soleimany Ferizhandy, A. (2011) "Platelet activation of platelet concentrates derived from buffy coat and apheresis methods", Transfusion and Apheresis Science, Vol.44, pp.11–13.
Sönmezoglu, M., Kocak, N., Öncul, O., Özbayburtlu, S., Hepgul, Z., Kosan, E. and Bayik, M. (2005) "Effects of a major earthquake on blood donor types and infectious diseases marker rates", Transfusion Medicine, Vol.15, No.2, pp.93-97.
Tofighi, S., Torabi, S. A. and Mansouri, S. A. (2016) "Humanitarian logistics network design under mixed uncertainty", European Journal of Operational Research, Vol.250, No.1, pp.239-250.
Torabi, S. A. and Hassini, E. (2008) "An interactive possibilistic programming approach for multiple objective supply chain master planning", Fuzzy Sets and Systems, Vol.159, No.2, pp.193-214.
Torabi, S. A. and Moghaddam, M. (2012) "Multi-site integrated production-distribution planning with trans-shipment: a fuzzy goal programming approach", International Journal of Production Research, Vol. 50, No.6, pp.1726-1748.
Vassallo, R. R. and Murphy, S. (2006) "A critical comparison of platelet preparation methods", Current Opinion in Hematology, Vol.13, No. 5, pp. 323-330.
Wang, K. M. and Ma, Z. J. (2015) "Age-based policy for blood transshipment during blood shortage". Transportation Research Part E: Logistics and Transportation Review, Vol.80, pp.166-183.
Zahiri, B., Torabi, S. A., Mousazadeh, M. and Mansouri, S. A. (2015) "Blood collection management: Methodology and application", Applied Mathematical Modelling, Vol. 39, No. 23, pp.7680-7696.
Zahiri, B., Mousazadeh, M. and Bozorgi-Amiri, A. (2014) "A robust stochastic programming approach for blood collection and distribution network design", International Journal of Research in Industrial Engineering, Vol.3, No.2, pp.1-11.
-
Arvan, M., Tavakkoli-Moghaddam, R. and Abdollahi, M. (2015) "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.
-
Beliën, J. and Forcé, H. (2012) "Supply chain management of blood products: A literature review", European Journal of Operational Research, Vol. 217, No. 1,  pp. 1-16.
-
Ben-Tal, A. and Nemirovski, A. (2000) "Robust solutions of linear programming problems contaminated with uncertain data", Mathematical Programming, Vol. 83, No. 3, pp. 411-424.
-
Bertolini F., Rebulla P., Porretti L. and Murphy S. (1992) "Platelet quality after 15-day storage of platelet concentrates prepared from buffy coats and stored in a glucose-free crystalloid medium", Transfusion, Vol. 32, pp.9–16.
-
Bertsimas, D. and Sim, M. (2004) "The price of robustness", Operations Research, Vol. 52, No. 1, pp.35-53.
-
Cheraghi, S. and Hosseini-Motlagh, S. M. (2017) "Optimal blood transportation in disaster relief considering facility disruption and route reliability under uncertainty", International Journal of Transportation Engineering, Vol. 4, No. 3, pp.225-254.
-
Dehghani, M. and Abbasi, B. (2018)"An age-based lateral-transshipment policy for perishable items", International Journal of Production Economics, Vol.198, pp.93-103.
-
Duan, Q. and Liao, T. W. (2014) "Optimization of blood supply chain with shortened shelf lives and ABO compatibility", International Journal of Production Economics, Vol.153, pp.113-129.
-
Eskandari-Khanghahi, M., Tavakkoli-Moghaddam, R., Taleizadeh, A. A. and Amin, S. H. (2018) "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.
-
Fischetti, Matteo and Michele Monaci (2009) "Light robustness", Robust and Online Large-scale Optimization, Springer Berlin Heidelberg, pp.61-84.    
-
Ghandforoush, P. and Sen, T. K. (2010) "A DSS to manage platelet production supply chain for regional blood centers", Decision Support Systems, Vol. 50, No.1, pp. 32-42.
-
Habibi-Kouchaksaraei, M., Paydar, M. M. and Asadi-Gangraj, E. (2018) "Designing a bi-objective multi-echelon robust blood supply chain in a disaster", Applied Mathematical Modelling, Vol.55, pp. 583-599.
-
Jabbarzadeh, A., Fahimnia, B. and 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, Vol.70, pp.225-244.
-
Jacobs, D. A., Silan, M. N. and Clemson, B. A. (1996) "An analysis of alternative locations and service areas of American Red Cross blood facilities", Interfaces, Vol.26, No.3, pp.40-50.
-
Kamyabniya, A., Lotfi, M. M., Naderpour, M. and Yih, Y. (2017) "Robust platelet logistics planning in disaster relief operations under uncertainty: A coordinated approach", Information Systems Frontiers, Vol. 20, No. 4, pp.1-24.
-
Khalilpourazari, S. and Khamseh, A. A. (2017)" Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application", Annals of Operations Research, pp.1-39.
-
Kohneh, J. N., Teymoury, E. and Pishvaee, M. S. (2016)" Blood products supply chain design considering disaster circumstances (Case study: Earthquake disaster in Tehran)", Journal of Industrial and Systems Engineering, Vol. 9, pp.51-72.
-
Levin, E., Culibrk,B., Gyöngyössy-Issa, M., Weiss, S., Scammell, K., LeFresne, W., Jenkins, C. and Devine, D. V. (2008) "Implementation of buffy coat platelet component production: comparison to platelet-rich plasma platelet production", Transfusion, Vol. 48, No.11, pp.2331-2337.
-
Melo, M. T., Nickel, S. and Saldanha-da-Gama, F. (2009) "Facility location and supply chain management–A review", European Journal of Operational Research, Vol.196, No. 2, pp.401-412.
-
Mousazadeh, M., Torabi, S. A. and Zahiri, B. (2015) "A robust possibilistic programming approach for pharmaceutical supply chain network design", Computers & Chemical Engineering, Vol.82, pp.115-128.
-
Mavrotas, G. (2009) "Effective implementation of the ε-constraint method in multi-objective mathematical programming problems", Applied Mathematics and Computation, Vol.213, No.2, pp.455-465.
-
Nagurney, A., Masoumi, A. H. and Yu, M. (2012) "Supply chain network operations management of a blood banking system with cost and risk minimization", Computational Management Science, Vol. 9, No.2, pp. 205-231.
-
Nahmias, S. (1982) "Perishable inventory theory: A review", Operations research, Vol.30, No. 4, pp. 680-708.
-
Osorio, A. F., Brailsford, S. C. and 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, Vol.53, No.24, pp.7191-7212.
-
Paterson, C., Teunter, R. and Glazebrook, K. (2012) "Enhanced lateral transshipments in a multi-location inventory system", European Journal of Operational Research, Vol.221, No. 2, pp. 317-327.
-
Pierskalla, W. P. (2005) "Supply chain management of blood banks", In Operations Research and Health Care (pp. 103-145). Springer, Boston, MA.
-
Prastacos, G. P. (1984) "Blood inventory management: an overview of theory and practice", Management Science, Vol. 30, No.7, pp. 777-800.
-
Ramezanian, R. and Behboodi, Z. (2017) "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.
-
Riahi, N., Hosseini-Motlagh, S. M. and Teimourpour, B. A. (2013) Three-phase hybrid times series modelling framework for improved hospital inventory demand forecast, International Journal of Hospital Research, Vol. 2, No. 3, pp. 133142.
-
Şahin, G., Süral, H. and Meral, S. (2007) "Locational analysis for regionalization of Turkish Red Crescent blood services", Computers & Operations Research, Vol.34, No.3, pp.692-704.
-
Salehi, F., Mahootchi, M. and Husseini, S. M. M. (2017)" Developing a robust stochastic model for designing a blood supply chain network in a crisis: A possible earthquake in Tehran", Annals of Operations Research, pp.1-25.
-
Samani, M. R. G., Torabi, S. A. and Hosseini-Motlagh, S. M. (2018) "Integrated blood supply chain planning for disaster relief".,International Journal of Disaster Risk Reduction, Vol. 27, pp.168-188.
-
Schreiber, G. B., Schlumpf, K. S., Glynn, S. A., Wright, D. J., Tu, Y., King, M. R., ... and Guiltinan, A. M. (2006) "Convenience, the bane of our existence, and other barriers to donating", Transfusion, Vol. 46, No.4, pp. 545-553.
-
Sha, Y. and Huang, J. (2012) "The multi-period location-allocation problem of engineering emergency blood supply systems", Systems Engineering Procedia, Vol. 5, pp.21-28.
-
Singh, C. (1982) "Convex programming with set-inclusive constraints and its applications to generalized linear and fractional programming", Journal of Optimization Theory and Applications, Vol.38, No.1, pp.33-42.
-
Soleimany Ferizhandy, A. (2011) "Platelet activation of platelet concentrates derived from buffy coat and apheresis methods", Transfusion and Apheresis Science, Vol.44, pp.11–13.
-
Sönmezoglu, M., Kocak, N., Öncul, O., Özbayburtlu, S., Hepgul, Z., Kosan, E. and Bayik, M. (2005) "Effects of a major earthquake on blood donor types and infectious diseases marker rates", Transfusion Medicine, Vol.15, No.2, pp.93-97.
-
Tofighi, S., Torabi, S. A. and Mansouri, S. A. (2016) "Humanitarian logistics network design under mixed uncertainty", European Journal of Operational Research, Vol.250, No.1, pp.239-250.
-
Torabi, S. A. and Hassini, E. (2008) "An interactive possibilistic programming approach for multiple objective supply chain master planning", Fuzzy Sets and Systems, Vol.159, No.2, pp.193-214.
-
Torabi, S. A. and Moghaddam, M. (2012) "Multi-site integrated production-distribution planning with trans-shipment: a fuzzy goal programming approach", International Journal of Production Research, Vol. 50, No.6, pp.1726-1748.
-
Vassallo, R. R. and Murphy, S. (2006) "A critical comparison of platelet preparation methods", Current Opinion in Hematology, Vol.13, No. 5, pp. 323-330.
-
Wang, K. M. and Ma, Z. J. (2015) "Age-based policy for blood transshipment during blood shortage". Transportation Research Part E: Logistics and Transportation Review, Vol.80, pp.166-183.
-
Zahiri, B., Torabi, S. A., Mousazadeh, M. and Mansouri, S. A. (2015) "Blood collection management: Methodology and application", Applied Mathematical Modelling, Vol. 39, No. 23, pp.7680-7696.
-
Zahiri, B., Mousazadeh, M. and Bozorgi-Amiri, A. (2014) "A robust stochastic programming approach for blood collection and distribution network design", International Journal of Research in Industrial Engineering, Vol.3, No.2, pp.1-11.