Designing blood supply chain networks with disruption considerations by a new interval-valued fuzzy mathematical model: M/M/C queueing approach

Abstract

The healthcare system of countries encounters several challenges during their performance, but the most significant one is to provide sufficient and safe required blood products for the individuals in need in the areas affected by disasters and to manage all of the aspects in those critical conditions. This paper presents a new multi-objective mathematical model to design an efficient blood supply chain in disasters considering temporary facilities along with fixed ones when it would be necessary and investigate potential disruptions both in blood facilities and links. Given the uncertainties caused by the arrival flows and to minimize the waiting time in blood banks (BBs), employing the queue theory leads the model to be efficient. Likewise, as the operations related to disaster responses deal with uncertainties, this paper presents a new extended interval-valued fuzzy (IVF) solution method based on weighted multi-choice goal programming (weighted MCGP) approach capable of helping decision-makers to set various weights for every goal and to find appropriate solutions. The optimization model is then solved by two metaheuristics, including genetic algorithm (GA) and red deer algorithm (RDA). Finally, the application of the proposed model is examined through a case study and numerical examples, and some managerial insights are provided based on the analysis of results.