2017 International Conference on Computer Science and Engineering (UBMK), Antalya, Türkiye, 5 - 08 Ekim 2017, ss.795-799
In this paper, we study Vehicle Routing Problem (VRP) for Blood Transporters (BTs) and propose an efficient vehicle routing scheme for blood transportation between hospitals or Donor/Client Sites (DCSs) within a region that is based on Artificial Intelligence. It is assumed that each BT in a fleet of vehicles starts and completes its route at a blood-bank while visiting a subset of DCSs using the shortest path. However, unlike traditional logistic planning, blood transportation may be time critical. Therefore, in our approach, the vehicle routing is formulated to take into account the urgency of the requests and responses. Consequently, the objective of this study is to minimize the number of BTs while maintaining their minimum traveling lengths considering priority. In this regards, we extended the classical Capacitated VRP (CVRP) and reformulated requests to take into account the priority by assigning weight to each request. A hybrid meta-heuristic algorithm including Genetic Algorithms and Local Search is used to simulate transporting blood requests of DCSs. We challenged our approach with symmetrical CVRP instances taken from literature. In this case study, we observed that both the cost and response time are reduced dramatically for emergency.