Abstract
The purpose of this study is to develop a pragmatic method for managing the inventory and production of blood platelets in places with inappropriate infrastructure. Thus far, we can find a rich number of papers regarding the optimization of blood products supply chain but most of them are impractical due to utilizing so many mathematical formulas and parameters. Hence, as an interdisciplinary study, we should develop a comprehensible method for medical workers and doctors to optimize the supply chain, maintain the quality of services and overcome the challenges. The inventory manager has to cope with multifaceted problems, among those are limited availability of donors, the uncertainty of demand, maintaining the quality and quantity of the products at a reasonable level and on-time response to medical centers and finally yet importantly avoid waste caused by overproduction. To tackle these problems, we employed Markov decision process and simulation to ensure the accountability of the model. Eventually, the real managerial insight provided through gathering data regarding the number of casualties caused by road accidents in Semnan province, Iran, and the number of blood platelet ordered by the hospitals and coordination between medical centers and the Blood Transfusion Center. The results indicate the accessibility of the model by inventory manager and physicians in the transfusion center and the reduction of waste due to appropriate production planning.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abdulwahab U, Wahab MIM (2014) Approximate dynamic programming modeling for a typical blood platelet bank. Comput Ind Eng 78:259–270. https://doi.org/10.1016/j.cie.2014.07.017
Albdulwahab US (2015) Blood platelet bank inventory management: an approximate dynamic programming approach. Ryerson University, Ryerson
Asllani A, Culler E, Ettkin L (2014) A simulation-based apheresis platelet inventory management model. Transfusion 54:2730–2735. https://doi.org/10.1111/trf.12570
Blake J, Heddle N, Hardy M, Barty R (2009) Simplified platelet ordering using shortage and outdate targets
Blake J, Heddle N, Hardy M, Barty R (2010) Simplified platelet ordering using shortage and outdate targets. Int J Health Plann Manag 1:144–156
Boucherie RJ, Van Dijk NM (2017) Markov decision processes in practice, vol 248. Springer, Berlin. https://doi.org/10.1007/978-3-319-47766-4
Chao X, Gong X, Shi C, Yang C, Zhang H, Zhou SX (2017) Approximation algorithms for capacitated perishable inventory systems with positive lead times. Manag Sci 64:5038–5061. https://doi.org/10.1287/mnsc.2017.2886
Chen J, Mao G, Li C, Liang W, Zhang D-G (2017) Capacity of cooperative vehicular networks with infrastructure support: multiuser case. IEEE Trans Veh Technol 67:1546–1560. https://doi.org/10.1109/TVT.2017.2753772
Chen S, Li Y, Zhou W (2019) Joint decisions for blood collection and platelet inventory control. Prod Oper Manag 28:1674–1691. https://doi.org/10.1111/poms.13009
Cheraghi S, Hosseini-Motlagh S-M (2018) Responsive and reliable injured-oriented blood supply chain for disaster relief: a real case study. Ann Oper Res. https://doi.org/10.1007/s10479-018-3050-5
Cheraghi S, Hosseini-Motlagh S-M, Ghatreh Samani M (2017) Integrated planning for blood platelet production: a robust optimization approach. J Ind Syst Eng 10:55–80
Civelek I, Karaesmen I, Scheller-Wolf A (2015) Blood platelet inventory management with protection levels. Eur J Oper Res 243:826–838. https://doi.org/10.1016/j.ejor.2015.01.023
Cui Y, Zhang D, Zhang T, Chen L, Piao M, Zhu H (2020) Novel method of mobile edge computation offloading based on evolutionary game strategy for IoT devices. AEU Int J Electron Commun 118:153134. https://doi.org/10.1016/j.aeue.2020.153134
Dalalah D, Bataineh O, Alkhaledi KA (2018) Platelets inventory management: a rolling horizon Sim-Opt approach for an age-differentiated demand. J Simul 13:209–225. https://doi.org/10.1080/17477778.2018.1497461
de Kort W, Janssen M, Kortbeek N, Jansen N, van der Wal J, van Dijk N (2011) Platelet pool inventory management: theory meets practice. Transfusion 51:2295–2303. https://doi.org/10.1111/j.1537-2995.2011.03190.x
Dehghani M, Abbasi B (2018) An age-based lateral-transshipment policy for perishable items. Int J Prod Econ 198:93–103. https://doi.org/10.1016/j.ijpe.2018.01.028
Dillon M, Oliveira F, Abbasi B (2017) A two-stage stochastic programming model for inventory management in the blood supply chain. Int J Prod Econ 187:27–41. https://doi.org/10.1016/j.ijpe.2017.02.006
Duan Q, Liao TW (2013) A new age-based replenishment policy for supply chain inventory optimization of highly perishable products. Int J Prod Econ 145:658–671. https://doi.org/10.1016/j.ijpe.2013.05.020
Duan J, Su Q, Zhu Y, Lu Y (2018a) Study on the centralization strategy of the blood allocation among different departments within a hospital. J Syst Sci Syst Eng 27:417–434. https://doi.org/10.1007/s11518-018-5377-5
Duan P, Mao G, Liang W, Zhang D (2018b) A unified spatio-temporal model for short-term traffic flow prediction. IEEE Trans Intell Transp Syst 20:3212–3223. https://doi.org/10.1109/TITS.2018.2873137
Ensafian H, Yaghoubi S (2017) Robust optimization model for integrated procurement, production and distribution in platelet supply chain. Transport Res Part E Logist Transport Rev 103:32–55. https://doi.org/10.1016/j.tre.2017.04.005
Ensafian H, Yaghoubi S, Yazdi MM (2017) Raising quality and safety of platelet transfusion services in a patient-based integrated supply chain under uncertainty. Comput Chem Eng 106:355–372. https://doi.org/10.1016/j.compchemeng.2017.06.015
Eskandari-Khanghahi M, Tavakkoli-Moghaddam R, Taleizadeh AA, Amin SH (2018) Designing and optimizing a sustainable supply chain network for a blood platelet bank under uncertainty. Eng Appl Artif Intell 71:236–250. https://doi.org/10.1016/j.engappai.2018.03.004
Gao J, Chen X, Yao K, Yang X (2017) Special issue on computational optimization and intelligence in uncertain environment. Springer, Berlin. https://doi.org/10.1007/s12652-017-0555-8
Ghandforoush P, Sen TK (2010) A DSS to manage platelet production supply chain for regional blood centers. Decis Support Syst 50:32–42. https://doi.org/10.1016/j.dss.2010.06.005
Gilani Larimi N, Yaghoubi S (2019) A robust mathematical model for platelet supply chain considering social announcements and blood extraction technologies. Comput Ind Eng 137:106014. https://doi.org/10.1016/j.cie.2019.106014
Gilani Larimi N, Yaghoubi S, Hosseini-Motlagh S-M (2019) Itemized platelet supply chain with lateral transshipment under uncertainty evaluating inappropriate output in laboratories. Soc Econ Plan Sci 68:100697. https://doi.org/10.1016/j.seps.2019.03.003
Gomez AT, Quinn JG, Doiron DJ, Watson S, Crocker BD, Cheng CKW (2015) Implementation of a novel real-time platelet inventory management system at a multi-site transfusion service. Transfusion 55:2070–2075. https://doi.org/10.1111/trf.13081
Guan L et al (2017) Big data modeling to predict platelet usage and minimize wastage in a tertiary care system. Proc Natl Acad Sci 114:11368–11373. https://doi.org/10.1073/pnas.1714097114
Guo Z, Liu Y, Liu Y (2017) Coordinating a three level supply chain under generalized parametric interval-valued distribution of uncertain demand. J Ambient Intell Human Computing 8:677–694. https://doi.org/10.1007/s12652-017-0472-x
Haijema R (2008) Source (or part of the following source): type PhD thesis title solving large structured Markov Decision Problems for perishable inventory management and traffic control. Amsterdam School of Economics Research Institute (ASE-RI)
Haijema R (2013) A new class of stock-level dependent ordering policies for perishables with a short maximum shelf life. Int J Prod Econ 143:434–439. https://doi.org/10.1016/j.ijpe.2011.05.021
Haijema R, van Dijk N, van der Wal J, Sibinga CS (2009) Blood platelet production with breaks: optimization by SDP and simulation. Int J Prod Econ 121:464–473. https://doi.org/10.1016/j.ijpe.2006.11.026
Hamdan B, Diabat A (2019) A two-stage multi-echelon stochastic blood supply chain problem. Comput Oper Res 101:130–143. https://doi.org/10.1016/j.cor.2018.09.001
Hamdan B, Diabat A (2020) Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation. Transport Res Part E Logist Transport Rev 134:101764. https://doi.org/10.1016/j.tre.2019.08.005
Hosseini-Motlagh S-M, Samani MRG, Homaei S (2020) Blood supply chain management: robust optimization, disruption risk, and blood group compatibility (a real-life case). J Ambient Intell Human Comput 11:1085–1104. https://doi.org/10.1007/s12652-019-01315-0
Kamyabniya A, Lotfi MM, Cai H, Hosseininasab H, Yaghoubi S, Yih Y (2019) A two-phase coordinated logistics planning approach to platelets provision in humanitarian relief operations IISE. Transactions 51:1–21. https://doi.org/10.1080/24725854.2018.1479901
Kouki C, Babai M, Minner S (2018) On the benefits of emergency orders in perishable inventory systems. Paper presented at the 19th international symposium on inventories
Larimi NG, Yaghoubi S, Hosseini-Motlagh S-M (2019) Itemized platelet supply chain with lateral transshipment under uncertainty evaluating inappropriate output in laboratories. Soc Econ Plan Sci 68:100697. https://doi.org/10.1016/j.seps.2019.03.003
Liu S, Zhang D-G, Liu X-H, Zhang T, Gao J-X, Cui Y-Y (2019a) Dynamic analysis for the average shortest path length of mobile ad hoc networks under random failure scenarios. IEEE Access 7:21343–21358. https://doi.org/10.1109/ACCESS.2019.2896699
Liu X-H, Zhang D-G, Yan H-R, Cui Y-Y, Chen L (2019b) A new algorithm of the best path selection based on machine learning. IEEE Access 7:126913–126928. https://doi.org/10.1109/ACCESS.2019.2939423
Liu S, Zhang D, Liu X, Zhang T, Wu H (2020) Adaptive repair algorithm for TORA routing protocol based on flood control strategy. Comput Commun. https://doi.org/10.1016/j.comcom.2020.01.024
Lowalekar H, Ravi RR (2017) Revolutionizing blood bank inventory management using the TOC thinking process: an Indian case study. Int J Prod Econ 186:89–122. https://doi.org/10.1016/j.ijpe.2017.02.003
Najafi M, Ahmadi A, Zolfagharinia H (2017) Blood inventory management in hospitals: considering supply and demand uncertainty and blood transshipment possibility. Oper Res Health Care 15:43–56. https://doi.org/10.1016/j.orhc.2017.08.006
Osorio AF, Brailsford SC, Smith HK, Forero-Matiz SP, Camacho-Rodríguez BA (2017) Simulation-optimization model for production planning in the blood supply chain. Health care Manag Sci 20:548–564. https://doi.org/10.1007/s10729-016-9370-6
Osorio AF, Brailsford SC, Smith HK, Blake J (2018) Designing the blood supply chain: how much, how and where? Vox Sang 113:760–769. https://doi.org/10.1111/vox.12706
Özener OÖ, Ekici A (2018) Managing platelet supply through improved routing of blood collection vehicles. Comput Oper Res 98:113–126. https://doi.org/10.1016/j.cor.2018.05.011
Özener OÖ, Ekici A, Çoban E (2019) Improving blood products supply through donation tailoring. Comput Oper Res 102:10–21. https://doi.org/10.1016/j.cor.2018.09.003
Rajendran S, Ravindran AR (2019) Inventory management of platelets along blood supply chain to minimize wastage and shortage. Comput Ind Eng 130:714–730. https://doi.org/10.1016/j.cie.2019.03.010
Ramezanian R, Behboodi Z (2017) Blood supply chain network design under uncertainties in supply and demand considering social aspects. Transport Res Part E Logist Transport Rev 104:69–82. https://doi.org/10.1016/j.tre.2017.06.004
Samani MRG, Hosseini-Motlagh S-M, Ghannadpour SF (2019) A multilateral perspective towards blood network design in an uncertain environment: methodology and implementation. Comput Ind Eng 130:450–471. https://doi.org/10.1016/j.cie.2019.02.049
Tan Y, Ji X, Yan S (2019) New models of supply chain network design by different decision criteria under hybrid uncertainties. J Ambient Intell Human Computing 10:2843–2853. https://doi.org/10.1007/s12652-018-1001-2
Yaghoubi S, Hosseini-Motlagh S-M, Cheraghi S, Larimi NG (2019) Designing a robust demand-differentiated platelet supply chain network under disruption and uncertainty. J Ambient Intell Human Comput. https://doi.org/10.1007/s12652-019-01501-0
Yang J, Ding M, Mao G, Lin Z, Zhang D-G, Luan TH (2019) Optimal base station antenna downtilt in downlink cellular networks. IEEE Trans Wirel Commun 18:1779–1791. https://doi.org/10.1109/TWC.2019.2897296
Zahiri B, Torabi SA, Mohammadi M, Aghabegloo M (2018) A multi-stage stochastic programming approach for blood supply chain planning. Comput Ind Eng 122:1–14. https://doi.org/10.1016/j.cie.2018.05.041
Zhang D-G (2012) A new approach and system for attentive mobile learning based on seamless migration. Appl Intell 36:75–89. https://doi.org/10.1007/s10489-010-0245-0
Zhang D-g, Zhang X-d (2012) Design and implementation of embedded un-interruptible power supply system (EUPSS) for web-based mobile application. Enterprise Inf Syst 6:473–489. https://doi.org/10.1080/17517575.2011.626872
Zhang D-G, Zhu Y-N, Zhao C-P, Dai W-B (2012) A new constructing approach for a weighted topology of wireless sensor networks based on local-world theory for the Internet of Things (IOT). Comput Math Appl 64:1044–1055. https://doi.org/10.1016/j.camwa.2012.03.023
Zhang D, Li G, Zheng K, Ming X, Pan Z-H (2013) An energy-balanced routing method based on forward-aware factor for wireless sensor networks. IEEE Trans Ind Inform 10:766–773. https://doi.org/10.1109/TII.2013.2250910
Zhang D, Wang X, Song X, Zhao D (2014) A novel approach to mapped correlation of ID for RFID anti-collision. IEEE Trans Serv Comput 7:741–748. https://doi.org/10.1109/TSC.2014.2370642
Zhang D-g, Wang X, Song X-d (2015a) New medical image fusion approach with coding based on SCD in wireless sensor network. J Electr Eng Technol 10:2384–2392. https://doi.org/10.5370/JEET.2015.10.6.2384
Zhang D-G, Wang X, Song X-D, Zhang T, Zhu Y-N (2015b) A new clustering routing method based on PECE for WSN EURASIP. J Wirel Commun Network 2015:162. https://doi.org/10.1186/s13638-015-0399-x
Zhang D-G, Zheng K, Zhang T, Wang X (2015c) A novel multicast routing method with minimum transmission for WSN of cloud computing service. Soft Comput 19:1817–1827. https://doi.org/10.1007/s00500-014-1366-x
Zhang D-g, Zheng K, Zhao D-X, Song X-d, Wang X (2016) Novel quick start (QS) method for optimization of TCP. Wirel Netw 22:211–222. https://doi.org/10.1007/s11276-015-0968-2
Zhang D-g, Liu S, Zhang T, Liang Z (2017a) Novel unequal clustering routing protocol considering energy balancing based on network partition and distance for mobile education. J Netw Comput Appl 88:1–9. https://doi.org/10.1016/j.jnca.2017.03.025
Zhang D-g, Niu H-l, Liu S (2017b) Novel PEECR-based clustering routing approach. Soft Comput 21:7313–7323. https://doi.org/10.1007/s00500-016-2270-3
Zhang D-g, Chen C, Cui Y-y, Zhang T (2018a) New method of energy efficient subcarrier allocation based on evolutionary game theory. Mob Netw Appl. https://doi.org/10.1007/s11036-018-1123-y
Zhang D-g, Tang Y-m, Cui Y-y, Gao J-x, Liu X-h, Zhang T (2018b) Novel reliable routing method for engineering of internet of vehicles based on graph theory. Eng Comput. https://doi.org/10.1108/EC-07-2018-0299
Zhang D-g, Zhang T, Dong Y, Liu X-h, Cui Y-y, Zhao D-x (2018c) Novel optimized link state routing protocol based on quantum genetic strategy for mobile learning. J Netw Comput Appl 122:37–49. https://doi.org/10.1016/j.jnca.2018.07.018
Zhang D-g, Zhang T, Zhang J, Dong Y, Zhang X-d (2018d) A kind of effective data aggregating method based on compressive sensing for wireless sensor network. EURASIP J Wirel Commun Netw 2018:1–15. https://doi.org/10.1186/s13638-018-1176-4
Zhang D-g, Zhou S, Tang Y-m (2018e) A low duty cycle efficient MAC protocol based on self-adaption and predictive strategy. Mob Netw Appl 23:828–839. https://doi.org/10.1007/s11036-017-0878-x
Zhang D, Ge H, Zhang T, Cui Y-Y, Liu X, Mao G (2018f) New multi-hop clustering algorithm for vehicular ad hoc networks. IEEE Trans Intell Transp Syst 20:1517–1530. https://doi.org/10.1109/TITS.2018.2853165
Zhang Dg, Liu S, Liu Xh, Zhang T, Cui Yy (2018g) Novel dynamic source routing protocol (DSR) based ongenetic algorithm-bacterial foraging optimization (GA-BFO). Int J Commun Syst 31:e3824. https://doi.org/10.1002/dac.3824
Zhang D-g, Gao J-x, Liu X-h, Zhang T, Zhao D-x (2019a) Novel approach of distributed and adaptive trust metrics for MANET. Wirel Netw 25:3587–3603. https://doi.org/10.1007/s11276-019-01955-2
Zhang D-g, Liu X-h, Cui Y-y, Chen L, Zhang T (2019b) A kind of novel RSAR protocol for mobile vehicular Ad hoc network CCF. Trans Netw 2:111–125. https://doi.org/10.1007/s42045-019-00019-5
Zhang D-G, Zhao P-Z, Cui Y-y, Chen L, Zhang T, Wu H (2019c) A new method of mobile ad hoc network routing based on greed forwarding improvement strategy. IEEE Access 7:158514–158524. https://doi.org/10.1109/ACCESS.2019.2950266
Zhang D, Gong C, Jiang K, Zhang X, Zhang T (2019d) A kind of new method of intelligent trust engineering metrics (ITEM) for application of mobile ad hoc network. Eng Comput. https://doi.org/10.1108/EC-12-2018-0579
Zhang D, Zhang T, Liu X (2019e) Novel self-adaptive routing service algorithm for application in VANET. Appl Intell 49:1866–1879. https://doi.org/10.1007/s10489-018-1368-y
Zhang D-g, Chen L, Zhang J, Chen J, Zhang T, Tang Y-m, Qiu J-n (2020a) A multi-path routing protocol based on link lifetime and energy consumption prediction for mobile edge computing. IEEE Access. https://doi.org/10.1109/ACCESS.2020.2986078
Zhang T, Zhang D, Qiu J, Zhang X, Zhao P, Gong C (2019f) A kind of novel method of power allocation with limited cross-tier interference for CRN. IEEE Access 7:82571–82583. https://doi.org/10.1109/ACCESS.2019.2921310
Zhang D-g, Wu H, Zhao P-z, Liu X-h, Cui Y-y, Chen L, Zhang T (2020b) New approach of multi-path reliable transmission for marginal wireless sensor network. Wirel Netw 26:1503–1517. https://doi.org/10.1007/s11276-019-02216-y
Zhu K, Shen J, Yao X (2019) A three-echelon supply chain with asymmetric information under uncertainty. J Ambient Intell Human Comput 10:579–591. https://doi.org/10.1007/s12652-018-0705-7
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Abbaspour, A., Jahan, A. & Rezaiee, M. A simple empirical model for blood platelet production and inventory management under uncertainty. J Ambient Intell Human Comput 12, 1783–1799 (2021). https://doi.org/10.1007/s12652-020-02254-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12652-020-02254-x