Ghane, M., Tavakkoli-Moghaddam, R. (2016). A stochastic optimization approach to a location-allocation problem of organ transplant centers. Journal of Optimization in Industrial Engineering, (), -.
Mahshid Ghane; Reza Tavakkoli-Moghaddam. "A stochastic optimization approach to a location-allocation problem of organ transplant centers". Journal of Optimization in Industrial Engineering, , , 2016, -.
Ghane, M., Tavakkoli-Moghaddam, R. (2016). 'A stochastic optimization approach to a location-allocation problem of organ transplant centers', Journal of Optimization in Industrial Engineering, (), pp. -.
Ghane, M., Tavakkoli-Moghaddam, R. A stochastic optimization approach to a location-allocation problem of organ transplant centers. Journal of Optimization in Industrial Engineering, 2016; (): -.
A stochastic optimization approach to a location-allocation problem of organ transplant centers
Articles in Press, Accepted Manuscript , Available Online from 26 December 2016
1Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran
2School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
Abstract
Decision making about location of critical resource on the geographical network is important in many industries, in the health care system these decisions include location of emergency and preventive care. The decisions of location play a crucial role because of determining the travel time between supply and demand points and response time in emergency activity. Organs are considered as highly perishable products, which verity of each has specific perish time. Despite all the importance of this field, only a small proportion of healthcare sector is dedicated to this field. Matching, finding the best recipient for a donated organ, is one of the major problem in this field which is also crucial for the overall organ transplantation process. Balancing the demand and supply in a transplant organ supply chain in order to decrease the waiting list needs certain scheduling and management. The main contribution of this paper consists of considering recipient regions as another component of the supply chain and importance of transportation time and waiting lists have led to consider a bi-objective model. In addition, uncertainty of input data has led to consider a stochastic approach.
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