VEHICLE ROUTING PROBLEM IN BLOOD DISTRIBUTION USING A HYBRID SWEEP ALGORITHM AND GENETIC ALGORITHM

Abstract

The Blood Supply Chain (BSC) presents significant logistical challenges due to the perishable nature and varied shelf lives of blood products. Efficient delivery route planning is crucial for optimizing blood distribution and enhancing overall operational efficiency. This study addressed the complex problem of determining optimal delivery routes using variants of the Vehicle Routing Problem (VRP): the Capacitated Vehicle Routing Problem (CVRP) and the Vehicle Routing Problem with Pick-Up and Delivery (VRPPD). The solution of CVRP and VRPPD was done by using metaheuristic methods, namely hybrid sweep algorithm and genetic algorithm. In addition, a numerical comparison was made using this proposed hybrid algorithm with a genetic algorithm, both applied to the same mathematical model. The comparative analysis revealed that the proposed hybrid algorithm generated 2 clusters with a total vehicle mileage of 225.60 km, whereas the genetic algorithm yielded 3 clusters with a total vehicle mileage of 248.80 km. The genetic algorithm resulted in a 10.28% (23.2 km) increase in total mileage compared to the proposed  hybrid algorithm, demonstrating the superior efficiency of the hybrid approach for optimizing blood delivery routes.