Blood supply chain: a two-stage approach for tactical and operational planning

Abstract

This work proposes a new integer linear programming model for tactical and operational planning of the blood supply chain. A two-stage approach is developed with a first aggregated stage to establish tactical planning decisions and a second disaggregated stage for the operational level. The model considers multi-products, multiperiods and perishability in a large planning horizon. Inventory levels as well as waste of whole blood and blood-derived products are also modelled. A purchase flow is introduced to handle situations of not enough collection to satisfy demand. The objective is cost minimisation whilst reducing waste and dependence on other regions through purchase. A case study of the South Region of Portugal is explored, demonstrating the possibility of decreased dependency and waste by adjusting allocation of facilities and allowing a more even distribution of activities between processing centres. This is the first study of the kind ever conducted on the Portuguese blood supply chain.

A stochastic bi-objective simulation–optimization model for plasma supply chain in case of COVID-19 outbreak

“…Araújo et al. [34] provided a two-level model for minimizing costs in blood supply chain. In the presented multi-commodity and multi-period model, strategic decisions were made at the first level and operational decisions at the second level.…”

“…Relative to the research done by Araújo et al. [34] , our study focused on the transportation capacity and substitution priority and estimating plasma demand using simulation. Haeri et al.…”

Blood inventory management: Ordering policies for hospital blood banks under uncertainty

“…(2018); Hamdan and Diabat (2019); Araújo et al. (2020); Rajendran and Srinivas (2020); Dehghani et al. (2021).…”

“…(2018), Hamdan and Diabat (2019), and Araújo et al. (2020) deal with more echelons besides the DN. The goal is to minimize the total system cost (Araújo et al., 2020) while maximizing the freshness of transported blood products to the hospitals (Zahiri et al., 2018) and minimizing wastage and blood delivery time (Hamdan and Diabat, 2019).…”

“…Since stochastic programming has proven to be an effective way to model uncertainty and because optimization techniques like this are less common in the context of blood inventory management, in this paper, we will address this gap while including some features that were not simultaneously considered before, such as safety stock and ABO-substitutions limit. The papers that apply stochastic programming and include inventory management decisions are Gunpinar and Centeno (2015); Dillon et al (2017); Zahiri et al (2018); Hamdan and Diabat (2019); Araújo et al (2020); Rajendran and Srinivas (2020); Dehghani et al (2021). Zahiri et al (2018), Hamdan andDiabat (2019), andAraújo et al (2020) deal with more echelons besides the DN.…”