Engineering and Applied Science Research (Jul 2023)
Logistic optimization of the blood delivery routing problem in the Lower Southern region of Thailand
Abstract
This study discusses a blood delivery routing problem faced by a regional blood centre (RBC). The RBC meets the requests of 21 hospitals for blood and blood products. Each hospital can request product deliveries throughout the day, but the RBC has a cut-off time for its transportation round and manually designates a specific route for the transport van, which is available only during working hours. This vehicle routing problem operates under vehicle time restriction constraints. The aim of the research is to use a metaheuristic method to find the optimal transport route to deliver blood and blood products at minimal total cost. This paper proposes a novel hybrid metaheuristic method that combines the firefly algorithm (FA) as the main structure, a crossover operator in differential evolution (DE) and a new local search (NLS); is called the HFA+NLS algorithm. The exact solution of the mathematical model and current practice are used for comparisons of the quality of the solutions. Four existing algorithms are also employed to compare the search performance. The paired t-test is used to compare the means of the search performance measures of any two methods. Different sizes of problem are considered by generating a set of nine test instances (small, medium and large problems) and a real-world case study to verify the competitive performance of the proposed algorithm. The computational results reveal that the HFA+NLS algorithm has a superior performance to other methods in the number of test instances for which the optimal, or the best known, solution was successfully found. The HFA+NLS algorithm determines the best route for a blood transport van with a total blood transportation cost reduction of 66.46%.
