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An exact criterion space search algorithm for a bi-objective blood collection problem

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  • Esmaeili, Somayeh
  • Bashiri, Mahdi
  • Amiri, Amirhossein

Abstract

Blood shortages are one of the main challenges in blood supply chains. To supply required blood, blood center managers face conflicting collection objectives involving costs and patients’ lives. Moreover, some challenging decisions must be made, such as routing, blood collection, location of blood stations, transshipment policy and holding inventory. In this study, a bi-objective mixed integer mathematical model is developed to address all the above-mentioned issues in the network. The model focuses on precisely determining the location of collection stations (permanent and temporary), transshipment and inventory of the blood center, routes and the quantity of collected blood to optimize the two objectives of decreasing total blood shortages and costs. Next, a subtour cut generation (SCG) method is introduced to enhance the solution approach of the problem. It leads to solving large instances more efficiently. The problem is critical and complex since missing even a non-dominated solution may lead to both negative financial impact and noncompensable outcomes. To extract all non-dominated solutions, an exact criterion space search method, called the triangle splitting method (TSM), is adopted. Several experiments are investigated for some instances from the literature. In addition, a real case study is considered. Results indicate that designing the network using the proposed mathematical model can significantly reduce total blood costs and shortages. Consequently, by utilizing the proposed methodology, blood center decision makers will have the opportunity to choose the most preferred point among extracted non-dominated solutions. Furthermore, the performance of the adopted TSM was compared with an improved non-dominated sorting genetic algorithm (NSGA-II) and lexmin epsilon constraint (LEPS). The results confirm that the adopted TSM algorithm performs much better than the improved NSGA-II and LEPS, considering bi-objective performance measures.

Suggested Citation

  • Esmaeili, Somayeh & Bashiri, Mahdi & Amiri, Amirhossein, 2023. "An exact criterion space search algorithm for a bi-objective blood collection problem," European Journal of Operational Research, Elsevier, vol. 311(1), pages 210-232.
    • Handle: RePEc:eee:ejores:v:311:y:2023:i:1:p:210-232
    DOI: 10.1016/j.ejor.2023.04.037
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    1. Chalmet, L. G. & Lemonidis, L. & Elzinga, D. J., 1986. "An algorithm for the bi-criterion integer programming problem," European Journal of Operational Research, Elsevier, vol. 25(2), pages 292-300, May.
    2. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    3. Hamdan, Bayan & Diabat, Ali, 2020. "Robust design of blood supply chains under risk of disruptions using Lagrangian relaxation," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 134(C).
    4. Behzad Zahiri & Mir Saman Pishvaee, 2017. "Blood supply chain network design considering blood group compatibility under uncertainty," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 2013-2033, April.
    5. Mohamadreza Fazli-Khalaf & Soheyl Khalilpourazari & Mohammad Mohammadi, 2019. "Mixed robust possibilistic flexible chance constraint optimization model for emergency blood supply chain network design," Annals of Operations Research, Springer, vol. 283(1), pages 1079-1109, December.
    6. Fahimnia, Behnam & Jabbarzadeh, Armin & Ghavamifar, Ali & Bell, Michael, 2017. "Supply chain design for efficient and effective blood supply in disasters," International Journal of Production Economics, Elsevier, vol. 183(PC), pages 700-709.
    7. Cavagnini, Rossana & Bertazzi, Luca & Maggioni, Francesca, 2022. "A rolling horizon approach for a multi-stage stochastic fixed-charge transportation problem with transshipment," European Journal of Operational Research, Elsevier, vol. 301(3), pages 912-922.
    8. Dehghani, Maryam & Abbasi, Babak, 2018. "An age-based lateral-transshipment policy for perishable items," International Journal of Production Economics, Elsevier, vol. 198(C), pages 93-103.
    9. Boland, Natashia & Charkhgard, Hadi & Savelsbergh, Martin, 2017. "The Quadrant Shrinking Method: A simple and efficient algorithm for solving tri-objective integer programs," European Journal of Operational Research, Elsevier, vol. 260(3), pages 873-885.
    10. Liu, Wenqian & Ke, Ginger Y. & Chen, Jian & Zhang, Lianmin, 2020. "Scheduling the distribution of blood products: A vendor-managed inventory routing approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    11. Javid Ghahremani-Nahr & Ramez Kian & Ehsan Sabet & Vahid Akbari, 2022. "A bi-objective blood supply chain model under uncertain donation, demand, capacity and cost: a robust possibilistic-necessity approach," Operational Research, Springer, vol. 22(5), pages 4685-4723, November.
    12. Alvarez, Aldair & Cordeau, Jean-François & Jans, Raf & Munari, Pedro & Morabito, Reinaldo, 2020. "Formulations, branch-and-cut and a hybrid heuristic algorithm for an inventory routing problem with perishable products," European Journal of Operational Research, Elsevier, vol. 283(2), pages 511-529.
    13. Masoumi, Amir H. & Yu, Min & Nagurney, Anna, 2017. "Mergers and acquisitions in blood banking systems: A supply chain network approach," International Journal of Production Economics, Elsevier, vol. 193(C), pages 406-421.
    14. Diabat, Ali & Jabbarzadeh, Armin & Khosrojerdi, Amir, 2019. "A perishable product supply chain network design problem with reliability and disruption considerations," International Journal of Production Economics, Elsevier, vol. 212(C), pages 125-138.
    15. Hosseini-Motlagh, Seyyed-Mahdi & Samani, Mohammad Reza Ghatreh & Homaei, Shamim, 2020. "Toward a coordination of inventory and distribution schedules for blood in disasters," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    16. Bertazzi, Luca & Chua, Geoffrey A. & Laganà, Demetrio & Paradiso, Rosario, 2022. "Analysis of effective sets of routes for the split-delivery periodic inventory routing problem," European Journal of Operational Research, Elsevier, vol. 298(2), pages 463-477.
    17. Soheyl Khalilpourazari & Shima Soltanzadeh & Gerhard-Wilhelm Weber & Sankar Kumar Roy, 2020. "Designing an efficient blood supply chain network in crisis: neural learning, optimization and case study," Annals of Operations Research, Springer, vol. 289(1), pages 123-152, June.
    18. Jorge, Jesús M., 2009. "An algorithm for optimizing a linear function over an integer efficient set," European Journal of Operational Research, Elsevier, vol. 195(1), pages 98-103, May.
    19. Bozkir, Cem D.C. & Ozmemis, Cagri & Kurbanzade, Ali Kaan & Balcik, Burcu & Gunes, Evrim D. & Tuglular, Serhan, 2023. "Capacity planning for effective cohorting of hemodialysis patients during the coronavirus pandemic: A case study," European Journal of Operational Research, Elsevier, vol. 304(1), pages 276-291.
    20. Y. P. Aneja & K. P. K. Nair, 1979. "Bicriteria Transportation Problem," Management Science, INFORMS, vol. 25(1), pages 73-78, January.
    21. Osorio, Andres F. & Brailsford, Sally C. & Smith, Honora K., 2018. "Whole blood or apheresis donations? A multi-objective stochastic optimization approach," European Journal of Operational Research, Elsevier, vol. 266(1), pages 193-204.
    22. Nagurney, Anna & Dutta, Pritha, 2019. "Competition for blood donations," Omega, Elsevier, vol. 85(C), pages 103-114.
    23. Dehghani, Maryam & Abbasi, Babak & Oliveira, Fabricio, 2021. "Proactive transshipment in the blood supply chain: A stochastic programming approach," Omega, Elsevier, vol. 98(C).
    24. Tirkolaee, Erfan Babaee & Golpîra, Hêriş & Javanmardan, Ahvan & Maihami, Reza, 2023. "A socio-economic optimization model for blood supply chain network design during the COVID-19 pandemic: An interactive possibilistic programming approach for a real case study," Socio-Economic Planning Sciences, Elsevier, vol. 85(C).
    25. Manousakis, Eleftherios & Repoussis, Panagiotis & Zachariadis, Emmanouil & Tarantilis, Christos, 2021. "Improved branch-and-cut for the Inventory Routing Problem based on a two-commodity flow formulation," European Journal of Operational Research, Elsevier, vol. 290(3), pages 870-885.
    26. Mavrotas, G. & Diakoulaki, D., 1998. "A branch and bound algorithm for mixed zero-one multiple objective linear programming," European Journal of Operational Research, Elsevier, vol. 107(3), pages 530-541, June.
    27. Kenneth E. Kendall & Sang M. Lee, 1980. "Formulating Blood Rotation Policies with Multiple Objectives," Management Science, INFORMS, vol. 26(11), pages 1145-1157, November.
    28. Natashia Boland & Hadi Charkhgard & Martin Savelsbergh, 2015. "A Criterion Space Search Algorithm for Biobjective Integer Programming: The Balanced Box Method," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 735-754, November.
    29. Agra, Agostinho & Christiansen, Marielle & Wolsey, Laurence, 2022. "Improved models for a single vehicle continuous-time inventory routing problem with pickups and deliveries," European Journal of Operational Research, Elsevier, vol. 297(1), pages 164-179.
    30. Natashia Boland & Hadi Charkhgard & Martin Savelsbergh, 2015. "A Criterion Space Search Algorithm for Biobjective Mixed Integer Programming: The Triangle Splitting Method," INFORMS Journal on Computing, INFORMS, vol. 27(4), pages 597-618, November.
    31. Archetti, Claudia & Ljubić, Ivana, 2022. "Comparison of formulations for the Inventory Routing Problem," European Journal of Operational Research, Elsevier, vol. 303(3), pages 997-1008.
    32. Samani, Mohammad Reza Ghatreh & Hosseini-Motlagh, Seyyed-Mahdi & Homaei, Shamim, 2020. "A reactive phase against disruptions for designing a proactive platelet supply network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 140(C).
    33. Soheyl Khalilpourazari & Alireza Arshadi Khamseh, 2019. "Bi-objective emergency blood supply chain network design in earthquake considering earthquake magnitude: a comprehensive study with real world application," Annals of Operations Research, Springer, vol. 283(1), pages 355-393, December.
    34. Olsson, Fredrik, 2010. "An inventory model with unidirectional lateral transshipments," European Journal of Operational Research, Elsevier, vol. 200(3), pages 725-732, February.
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