An Evolutionary-Based Optimization for a Multi-Objective Blood Banking Supply Chain Model

Abstract

The study is focused both on the Location-Allocation Problem and the inventory control problem for a blood banking supply chain. We consider a two-echelon supply chain in which each regional blood center (RBC) sends blood to different CBCs and then delivers it to different allocated hospital blood banks (HBBs). According to the perishable characteristic of blood product, we design a two-staged approach including two models. In strategic stage, we propose model 1 to obtain the location-allocation decisions by determining (a) how many community blood centers (CBCs) should be in an area and (b) where they should be located and (c) which services should be assigned to which CBCs. In tactic stage, we implement model 2 to acquire the inventory control decisions of the optimal blood replenishment quantity and the optimal length of blood order cycle for each CBC. In additions, two objectives are used to construct model 1 so as to make the total supply chain cost the smallest and responsiveness level the biggest, not just a single objective. To solve this multiple objectives programming problem, we use a non-dominated Sorting Genetic Algorithm II (NSGA-II) to search for the Pareto set. MATLAB was implemented to solve our established models. Some computational results for the models using the actual data from all Regional Blood Organizations in Taiwan are derived.