Optimization of Blood Bag Distribution Routes Using AMPL Software and Nearest Neighbor Algorithm (Case Study of the Indonesian Red Cross Jakarta)

Abstract

The process of distributing blood bags by the Indonesian Red Cross (PMI) DKI Jakarta uses route selection preferences by ambulance drivers. Basically, this routing problem can impact other aspects such as additional costs, distribution time, fuel use, carbon emissions, and others, so this research needs to propose the best route to minimize travel distance. There are several Hospital Blood Banks (BDRS) in Jakarta that do not receive blood bags at the right time. As an organization authorized to provide blood bag supply, the PMI must distribute blood bag using the 7R concept (Right Time, Right Place, Right Quantity, Right Quality, Right Cost, Right Condition, and Right People). The PMI also has to consider that blood bags are classified as perishable items that need to require fast and precise handling. Therefore, it is necessary to optimize the blood distribution by minimizing travel distance. The optimization model used is the Vehicle Routing Problem (VRP) with AMPL software comparing with the Nearest Neighbor (NN) algorithm. After 4 hours of running the trial, this research has revealed that AMPL software gives the best combination of travel distance than the Nearest Neighbor algorithm, with the differences being approximately 11.52 km.