Dynamic multi-depot vehicle routing problem in the era of Industry 4.0

Abstract

The ongoing challenge for supply chain systems is accommodating real-time changes and unpredictable demands from system entities or customers. In a dynamic commodity delivery system, new orders enter the system while the vehicles are already on-route deliver scheduled orders. The critical problem in such cases is developing the intelligence to dynamically respond to changing demands while minimising transportation costs. In this research, an innovative Industry 4.0 approach was used to suggest a solution to 'dynamic multi-depot vehicle routing problem (DMDVRP)'. This research was designed to optimise the transportation expenses while maintaining each vehicle capacity constraint as serving customer stochastic demands from multiple depots. Industry 4.0 is a new implementation of technology utilised by companies, in this case, to bring around a transformed supply chain solution and system with a dynamic approach. Two-stage hybrid algorithms were developed for solving the DMDVRP. The experimental scenarios' results demonstrate the developed algorithms were effective.