Robust and stable flexible blood supply chain network design under motivational initiatives. (June 2020)

• Record Type: Journal Article
• Authors: Hosseini-Motlagh, Seyyed-Mahdi; Samani, Mohammad Reza Ghatreh; Cheraghi, Sara
• Is Part Of: Socio-economic planning sciences. Number 70(2020)
• Publication Date: 2020-06
• Subjects: Blood supply chain -- Motivational initiatives -- Data envelopment analysis -- Flexible programming -- Possibilistic programming -- P-robustness; Planning -- Periodicals; Economic policy -- Periodicals; Social policy -- Periodicals; Planification -- Périodiques; Politique économique -- Périodiques; Politique sociale -- Périodiques; ECONOMIC PLANNING; SOCIAL PLANNING; DECISION-MAKING; 361
• DOI: 10.1016/j.seps.2019.07.001
• Languages: English
• ISSNs: 0038-0121

Abstract

Abstract: To improve the coordination of blood supply and demand, the efficient design of the blood supply chain network (BSCN) is a proper strategy. In this regard, this paper is the first-ever study to strive for a simultaneous investigation on three interdependent challenges of the BSCN: (1) donors motivation, (2) optimizing location and capacity decisions, and (3) controlling the reliability and robustness of the network under combinatorial risk. As in reality, blood donors play a critical role in the BSC; this study undertakes motivational initiatives to encourage blood donors for maintaining sufficient blood supply. Advertisement, education and medical credits are the directions incorporated to construct the motivational function. To observe the efficiency as the most critical factor while evaluating the pool of location alternatives for establishing facilities, an augmented version of data envelopment analysis (DEA) is utilized. In addition, a mixed integer programming model is proposed by which the simultaneous location and capacity decisions are supported. The model is also extended to handle the combinatorial risk of uncertainty as well as disruption. Thus, a novel mixed possibilistic-stochastic flexible robust programming (MPSFRP) is developed. Eventually, the proposed model is implemented in a real case study to assess its practicality and then provide applicable insights for administrators. Highlights: A bi-product BSCN is addressed while incorporating location and capacity decisions. Motivational efforts have been suggested to encourage blood donation. An augmented DEA model is utilized to determine most efficient candidate locations. A novel mixed possibilistic-stochastic flexible robust model is proposed. A real case study is utilized to investigate the practicality of the model.