جستجوی مقالات مرتبط با کلیدواژه « Blood supply chain » در نشریات گروه « عمران »

Management of blood products is one of the major concerns of mankind. Although efforts have been made to find suitable alternatives to blood, but blood donors are still the most important source of care for patients. Blood is a sensitive and perishable product; in addition, a little it’s randomness of supply and demand can add to the complexity of this chain and make it difficult to manage, especially in earthquake-prone situations, because its deficiency causes human death and excess is not accepted. Therefore, in this paper, a mathematical model for locating blood distribution sites along with transporting vehicles routing in earthquake conditions is presented. The goals are to minimize blood shortages, maximize satisfaction of affected people, and minimize transportation and location costs. One of the contributions of this paper is considering scenario-based uncertainty along with risk of disturbance and satisfaction of affected people. The proposed model is solved in small and medium dimensions with the Epsilon constraint algorithm and for the case study (District 7 of Tehran city) with the non-dominated sorting genetic algorithm (NSGA). The results of the analysis show that the estimation error is minimized in the non-dominated sorting genetic algorithm and as the number of established distribution centers increases with demand increases.

Possessing a considerable portion of the cost of any health system, blood supply chain is one of the most critical parts of the system. Accordingly, any improvement in the performance of a blood supply chain can result in significantly improved performance as well as cost of the health systems. To have an efficient blood supply chain, appropriate planning is of great significance. This paper puts forward a bi-objective mixed-integer linear programming model for designing blood collection, production, inventory control and distribution under uncertainty with the need for making both strategic and tactical decisions simultaneously over multiple periods of planning. Moreover, blood transshipment between regional blood centers is accounted for in this work. To deal with the proposed bi-objective model, the epsilon-constraint method is devised, and to capture demand uncertainty, a Light robust approach is applied. The usefulness of the concerned model and its solution technique, which is a combination of epsilon-constraint and Light robust methods, is then evaluated via a set of numerical examples, and also, the sensitivity analysis is provided. We close the research while comparing the performance of both deterministic and robust models based on the network total cost, a performance measure including both constraint violation cost (feasibility robustness) and objective functions (optimality robustness) under a specific realization. The results imply that the robust approach strongly outperforms the deterministic one.