Mathematical modelling
Alireza Hamidieh; Ali Johari
Abstract
The growing need for adequate and safe blood and the high costs of health systems have prompted governments to improve the functioning of health systems. One of the most critical parts of a health system is the blood supply chain, which accounts for a significant share of the health system's costs. In ...
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The growing need for adequate and safe blood and the high costs of health systems have prompted governments to improve the functioning of health systems. One of the most critical parts of a health system is the blood supply chain, which accounts for a significant share of the health system's costs. In the present study, with an operational approach, the total network costs are minimized along with the minimization of transportation time and lead time of delivery of blood products. Also, determining the optimal routing decisions is improved the level of responsiveness and reliability of the network. In this research, a multi-objective stochastic nonlinear mixed-integer model has been developed for Tehran's blood supply chain network. Robust scenario-based programming is capable of effectively controlling parametric uncertainty and the level of risk aversion of network decisions. Also, the proposed reliability approach controls the adverse effects of disturbances and creates an adequate confidence level in the capacity of the network blood bank. Lastly, the model is solved through the Lagrangian relaxation algorithm. Comparison of the results shows the high convergence rate of the solutions in the Lagrangian relaxation algorithm.
B. Zahiri; M. Mousazadeh; A. Bozorgi-Amiri
Volume 3, Issue 2 , May 2014, , Pages 1-11
Abstract
Blood supply chain network design isanessentialpart of the total blood management systems.In this paper, a mixed integer non-linear programming (MINLP) model for the concerned problem is developed. Optimizing the facility location and flows between each echelon of the considered supply chain is our main ...
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Blood supply chain network design isanessentialpart of the total blood management systems.In this paper, a mixed integer non-linear programming (MINLP) model for the concerned problem is developed. Optimizing the facility location and flows between each echelon of the considered supply chain is our main focus in this study. Also, in order to handle uncertain nature of model parameters, a mix robust stochastic programming approach is applied to the model. Finally, to test the applicability of the proposed model, a numerical example is proposed using random generated data and then sensitivity analysis is done on a model parameter which play a rolein making trade-off between model robustness and optimality robustness.
