Processing, Please wait...

  • Home
  • About Us
  • Search:
  • Advanced Search

Growing Science » International Journal of Industrial Engineering Computations » Periodic blood inventory system with two supplies and two priority demand classes

Journals

  • IJIEC (747)
  • MSL (2643)
  • DSL (668)
  • CCL (508)
  • USCM (1092)
  • ESM (413)
  • AC (562)
  • JPM (271)
  • IJDS (912)
  • JFS (91)
  • HE (32)
  • SCI (26)

IJIEC Volumes

    • Volume 1 (17)
      • Issue 1 (9)
      • Issue 2 (8)
    • Volume 2 (68)
      • Issue 1 (12)
      • Issue 2 (20)
      • Issue 3 (20)
      • Issue 4 (16)
    • Volume 3 (76)
      • Issue 1 (9)
      • Issue 2 (15)
      • Issue 3 (20)
      • Issue 4 (12)
      • Issue 5 (20)
    • Volume 4 (50)
      • Issue 1 (14)
      • Issue 2 (10)
      • Issue 3 (12)
      • Issue 4 (14)
    • Volume 5 (47)
      • Issue 1 (13)
      • Issue 2 (12)
      • Issue 3 (12)
      • Issue 4 (10)
    • Volume 6 (39)
      • Issue 1 (7)
      • Issue 2 (12)
      • Issue 3 (10)
      • Issue 4 (10)
    • Volume 7 (47)
      • Issue 1 (10)
      • Issue 2 (14)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 8 (30)
      • Issue 1 (9)
      • Issue 2 (7)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 9 (32)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (7)
      • Issue 4 (10)
    • Volume 10 (34)
      • Issue 1 (8)
      • Issue 2 (10)
      • Issue 3 (8)
      • Issue 4 (8)
    • Volume 11 (36)
      • Issue 1 (9)
      • Issue 2 (8)
      • Issue 3 (9)
      • Issue 4 (10)
    • Volume 12 (29)
      • Issue 1 (9)
      • Issue 2 (6)
      • Issue 3 (8)
      • Issue 4 (6)
    • Volume 13 (41)
      • Issue 1 (10)
      • Issue 2 (8)
      • Issue 3 (10)
      • Issue 4 (13)
    • Volume 14 (50)
      • Issue 1 (11)
      • Issue 2 (15)
      • Issue 3 (9)
      • Issue 4 (15)
    • Volume 15 (55)
      • Issue 1 (19)
      • Issue 2 (15)
      • Issue 3 (12)
      • Issue 4 (9)
    • Volume 16 (75)
      • Issue 1 (12)
      • Issue 2 (15)
      • Issue 3 (19)
      • Issue 4 (29)
    • Volume 17 (21)
      • Issue 1 (21)

Keywords

Supply chain management(166)
Jordan(161)
Vietnam(149)
Customer satisfaction(120)
Performance(113)
Supply chain(110)
Service quality(98)
Competitive advantage(95)
Tehran Stock Exchange(94)
SMEs(87)
optimization(86)
Financial performance(83)
Trust(83)
TOPSIS(83)
Sustainability(81)
Job satisfaction(80)
Factor analysis(78)
Social media(78)
Knowledge Management(77)
Artificial intelligence(77)


» Show all keywords

Authors

Naser Azad(82)
Mohammad Reza Iravani(64)
Zeplin Jiwa Husada Tarigan(63)
Endri Endri(45)
Muhammad Alshurideh(42)
Hotlan Siagian(39)
Jumadil Saputra(36)
Dmaithan Almajali(36)
Muhammad Turki Alshurideh(35)
Barween Al Kurdi(32)
Ahmad Makui(32)
Basrowi Basrowi(31)
Hassan Ghodrati(31)
Mohammad Khodaei Valahzaghard(30)
Sautma Ronni Basana(29)
Shankar Chakraborty(29)
Ni Nyoman Kerti Yasa(29)
Sulieman Ibraheem Shelash Al-Hawary(28)
Prasadja Ricardianto(28)
Haitham M. Alzoubi(27)


» Show all authors

Countries

Iran(2183)
Indonesia(1290)
India(787)
Jordan(786)
Vietnam(504)
Saudi Arabia(453)
Malaysia(441)
United Arab Emirates(220)
China(206)
Thailand(153)
United States(111)
Turkey(106)
Ukraine(104)
Egypt(98)
Canada(92)
Peru(88)
Pakistan(85)
United Kingdom(80)
Morocco(79)
Nigeria(78)


» Show all countries

International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 14 Issue 2 pp. 201-220 , 2023

Periodic blood inventory system with two supplies and two priority demand classes Pages 201-220 Right click to download the paper Download PDF

Authors: Kanchala Sudtachat, Sunarin Chanta, Arjaree Saengsathien

DOI: 10.5267/j.ijiec.2023.2.005

Keywords: Blood inventory, Perishable inventory, Finite horizon, Dynamic programming, Healthcare

Abstract: Managing blood inventory is challenging due to the perishable and unstable nature of the product needed for transfusions in healthcare facilities. In this paper, we consider a periodic review blood inventory model with two priority demand classes, namely emergency and regular patients. We propose a dynamic programming model for determining the optimal ordering policy at the hospital given the uncertainty regarding received donated blood units. The optimal policy deals with placing orders for blood units that will expire within a fixed period. The objective is to minimize total expected costs within a planning horizon while maintaining a specified expected service level. Our model considers uncertain demands and donated blood units with discrete probability following known distributions. A tabu search algorithm is developed for large-scale problems. The performance of these ordering policies is compared against the optimal fixed order quantity and the order up-to-level policies using real-life data. The numerical results show the benefit of our model over the optimal fixed order quantity and the order up-to-level policies. We measure the total expected cost and the expected service level obtained from the optimal and near-optimal policies and provide a sensitivity analysis on parameters of interest.

How to cite this paper
Sudtachat, K., Chanta, S & Saengsathien, A. (2023). Periodic blood inventory system with two supplies and two priority demand classes.International Journal of Industrial Engineering Computations , 14(2), 201-220.

Refrences
American Red Cross, Facts About Blood Needs (2021). Accessed on 2 August 2021. https://www.redcrossblood.org.
Arani, M., Chan, Y., Liu, X. & Momenitabar, M. (2021). A lateral resupply blood supply chain network design under uncertainties. Applied Mathematical Modelling, 93, 165-187.
Bakker, M., Jan, R. & Ruud, H. T. (2012). Review of inventory systems with deterioration since 2001. European Journal of Operational Research, 221(2), 275-284.
Chazan, D. & Gal, S. (1977). A markovian model for a perishable product inventory. Management Science, 23(5), 512-521.
Chiu, H. N. (1995). A heuristic (R, T) periodic review perishable inventory model with lead times. International Journal of Production Economics, 42(1), 1-15.
Civelek, I., Karaesmen, I. & Scheller-Wolf, A. (2015). Blood platelet inventory management with protection levels. European Journal of Operational Research, 243(3), 826-838.
Cohen, M. A. (1976). Analysis of single critical number ordering policies for perishable inventory. Operations Research, 24(4), 726-741.
Cooper, W. L. (2001). Path wish properties and performance bounds for a perishable inventory system. Operation Research, 49(3), 455-466.
Daroudi, S., Kazemipoor, H., Najafi, H. & Fallah, M. (2021). The minimum latency in location routing fuzzy inventory problem for perishable multi-product materials. Applied Soft Computing, 110, 107543.
Dai, Z., Gao, K. & Zheng, X. (2020). Optimizing two multi-echelon inventory systems for perishable products with price and stock dependent demand in supply chain. Scientia Iranica E, 29(1), 320-342.
Dillon, M., Oliveira, F. & Abbasia, B. (2017). A two-stage stochastic programming model for inventory management in the blood supply chain. International Journal of Production Economics, 187, 27-41.
Dillon, M., Oliveira, F. & Abbasi, B. (2017). A two-stage stochastic programming model for inventory management in the blood supply chain. International Journal of Production Economics, 187, 27-41.
Gitinavard, H., Ghodsypour, S. H. & Shirazi, M.A. (2019). A bi-objective multi-echelon supply chain model with Pareto optimal points evaluation for perishable products under uncertainty. Scientia Iranica E, 26(5), 2952-2970.
Gunpinar, S.& Centeno, G. (2015). Stochastic integer programming models for reducing wastages and shortages of blood products at hospitals. Computers & Operations Research, 54, 129-141.
Gupta, A. M., Ojha, S., Nagaraju, P., Poojary, M., Sumathi, S. H., Sathyan, V. & Ansari, A. (2021). Impact of the novel coronavirus disease and lockdown on the packed red blood cells inventory management: An experience from a tertiary care oncology center in Western India. Hematology, Transfusion and Cell Therapy, 43(2), 126-132 .
Haijema, R., Wal, J. & Dijk, N. M. (2007). Blood platelet production: Optimization by dynamic programming and simulation. Computers and Operations Research, 34(3), 760-779.
Heidari-Fathian, H. & Pasandideh, S. H. R. (2018). Green-blood supply chain network design: Robust optimization, bounded objective function & Lagrangian relaxation. Computers & Industrial Engineering, 122, 95-105.
Hosseinifard, Z. & Abbasi, B. (2018). The inventory centralization impacts on sustainability of the bloodsupply chain. Computers & Operations Research, 89, 206-212.
Janssena, L., Diabat, A., Sauerd, J. & Herrmann, F. (2018). A stochastic micro-periodic age-based inventory replenishment policy for perishable goods. Transportation Research Part E, 118, 445-465.
Karaesmen, I. Z., Alan, S. & Borga, D. (2011). Managing perishable and aging inventories: review and future research directions, In Planning production and inventories in the extended enterprise, Springer, New York, NY, 393-436.
Kouki, C., Sahin, E., Jemai, Z. & Dallery, Y. (2010). Periodic review inventory policy for perishables with random lifetime, 8th International conference of modeling and simulation.
Liu, W., Ke, G. Y., Chen, J. & Zhang, L. (2020). Scheduling the distribution of blood products: A vendor-managed inventory routing approach. Transportation Research Part E: Logistics and Transportation Review, 140, 101964.
Lowalekar, H. & Ravic, R. R. (2017). Revolutionizing blood bank inventory management using the TOC thinking process: An Indian case study. International Journal of Production Economics, 186, 89-122.
Meng, Q., Guo, Y. & Zhang, X., (2021). Mitigation strategies for expiration in perishable emergency inventory system. Computers & Industrial Engineering, 157, 107336.
Minner, S. & Transchel, S. (2010). Periodic review inventory-control for perishable products under service-level constraints. OR Spectrum, 32(4), 979-996.
Mokhtar, S., Bahri, P.A. & Shahnazari, M. (2021). Inventory strategy development under supply disruption risk. Computers & Industrial Engineering, 161, 107662.
Montgomery, C. D. (1997). Design and Analysis of Experiments, 5th Edition., John Wiley & Sons, Inc., 456-466.
Nahmias, S. (1975). Ordering policies for perishable inventory II. Operations Research, 23(4), 735-749.
Nahmias, S. (1976). Approximations for the perishable inventory problem. Management Science, 22(9), 1002-1008.
Nahmias, S. (1978). The fixed-charge perishable inventory problem. Operations Research, 26(3), 464-481.
Nahmias, S. (1982). Perishable inventory theory: A review. Operations Research, 30(4), 680-708.
Nahmias, S. (2011). Perishable inventory systems. Springer Science & Business Media, Vol. 160.
Nahmias, S. (1977). On ordering perishable inventory when both demand and lifetime are random. Management Science, 24(1), 82-90.
Nahmias, S. & Schmidt, C. P. (1986). An application of the theory of weak convergence to the dynamic perishable inventory. Mathematics of Operations Research, 11(1), 62-69.
Nandakumar, P. & Morton, T. E. (1993). Near myopic heuristics for the fixed-life perishability problem. Management science, 39(12), 1490-1498.
Ng, M. S. Y., David, M., Middelburg, R. A., Ng, A. S. Y., Suen, J. Y., Tung, J. & Fraser, J. F. (2018). Transfusion of packed red blood cells at the end of shelf life is associated with increased risk of mortality – a pooled patient data analysis of 16 observational trials. Haematologica, 109(9), 1542-1548.
Pierskalla, W. P. (1972). Optimal issuing policies for perishable inventory. Management science, 18(11), 603-614.
Prastacos, G. P. (1984). Blood inventory management: an overview of theory and practice. Management science, 30(7), 777-800.
Rajendran, S. & Ravindran, A. R. (2017). Platelet ordering policies at hospitals using stochastic integer programming model and heuristic approaches to reduce wastage. Computers & Industrial Engineering, 110, 151-164.
Sohrabi, M., Zandieh, M. & Afshar-Nadjafi, B. An equity-oriented multi-objective inventory management model for blood banks considering the patient condition: A real-life case. Articles in Press, Scientia Iran, Available Online from 07 July 2021.
The American Red Cross, Facts About Blood Needs (2021). Accessed on 2 August 2021, https://www.redcrossblood.org.
Williams, C. L. & Patuwo, B. E. (1999). A perishable inventory model with positive order lead times. European Journal of Operational Research, 116(2), 352-373.
Yavari, M., Enjavi, H., & Geraeli, M., (2020). Demand management to cope with routes disruptions in location-inventory routing problem for perishable products. Research in Transportation Business & Management, 37, 100552.
Zahiri, B., Torabi, S. A., Mousazadeh, M. & Mansouri, S. A. (2015). Blood collection management: Methodology and application. Applied Mathematical Modelling, 39(23-24), 7680-7696.
Zhou, Y., Zou, T., Liu, C., Yu, H., Chen, L. & Su, L. (2021). Blood supply chain operation considering lifetime and transshipment under uncertain environment. Applied Soft Computing, 106, 107364.
  • 17
  • 1
  • 2
  • 3
  • 4
  • 5

Journal: International Journal of Industrial Engineering Computations | Year: 2023 | Volume: 14 | Issue: 2 | Views: 1074 | Reviews: 0

Related Articles:
  • A decision model for an inventory system with two compound Poisson demands
  • A two-stage production planning model for perishable products under uncerta ...
  • An integrated production inventory model of deteriorating items subject to ...
  • A robust optimization model for blood supply chain in emergency situations
  • Designing a bi-objective and multi-product supply chain network for the sup ...

Add Reviews

Name:*
E-Mail:
Review:
Bold Italic Underline Strike | Align left Center Align right | Insert smilies Insert link URLInsert protected URL Select color | Add Hidden Text Insert Quote Convert selected text from selection to Cyrillic (Russian) alphabet Insert spoiler
winkwinkedsmileam
belayfeelfellowlaughing
lollovenorecourse
requestsadtonguewassat
cryingwhatbullyangry
Security Code: *
Include security image CAPCHA.
Refresh Code

® 2010-2026 GrowingScience.Com