A Three-Stage Algorithm for the Large Scale Dynamic Vehicle Routing Problem with an Industry 4.0 Approach
This addresses efficient logistics for companies with dynamic supply chains, though it appears incremental as it builds on existing clustering and routing methods.
The paper tackled the large-scale dynamic vehicle routing problem (LSDVRP) by proposing a three-stage hierarchical algorithm to minimize transit costs under capacity constraints, and the results confirmed its applicability for real-world problems.
Companies are eager to have a smart supply chain especially when they have a dynamic system. Industry 4.0 is a concept which concentrates on mobility and real-time integration. Thus, it can be considered as a necessary component that has to be implemented for a Dynamic Vehicle Routing Problem. The aim of this research is to solve large-scale DVRP (LSDVRP) in which the delivery vehicles must serve customer demands from a common depot to minimize transit cost while not exceeding the capacity constraint of each vehicle. In LSDVRP, it is difficult to get an exact solution and the computational time complexity grows exponentially. To find near optimal answers for this problem, a hierarchical approach consisting of three stages callled cluster first, route construction second, route improvement third is proposed. The major contribution of this paper is dealing with large-size real-world problems to decrease the computational time complexity. The results confirmed that the proposed methodology is applicable.