Modeling and optimizing a blood supply chain network in crisis considering blood compatibility using Non-dominated Sorting Genetic Algorithm- II, a case study in Tehran

Due to the critical role and importance of blood products in human life, especially in emergency situations such as earthquake, designing an efficient blood supply chain is essential especially considering real world assumptions including blood compatibility. This Research proposes a multi-objective model for emergency blood supply chainmanagement considering blood compatibility, routing, and locationallocation decisions. The blood supply chain network consists of five different echelons including donors, collection facilities, laboratories, blood centers, and hospitals. The mathematical model aims to minimize total supply chain cost and time while maximizing minimum reliability of established routes by making decisions regarding location-allocation, blood flow, inventory levels, and optimal routes. In order to solve the problem, a classic and efficient meta heuristic algorithm, Nondominated Sorting Genetic Algorithm- II, is used. Performance of the algorithm is evaluated in various test problems using powerful measures. Also, the application of the proposed model is investigated in a case study in Iran’s capital, Tehran. Based on the results, important managerial insights are derived and optimal locations for facilities, inventory levels, routes and blood flow between facilities are determined.

Keywords:

Blood Supply Chain , Disaster Management , Multi-Objective Optimization , Supply Chain Management , Meta-Heuristic algorithms