On the Development of a Multilayered Agent-based Heuristic System for Vehicle Routing Problem under Random Vehicle Breakdown

With the recent technological advancement, the Dynamic Vehicle Routing Problem is becoming more applicable. However, almost all of the researches in this field limited the source of dynamism from the order side instead of the vehicle and the adoption of inflexible tools that are mainly designed for the static problem, considering multiple random vehicle breakdowns complicate how to adapt and distribute the workload to other functioning vehicles. In this ongoing PhD research, a proposed multilayered agent-based model (ABM) and a
modeling framework on dealing with such disruptive events in a continuous reactive manner. The model is partially constructed and experimented, with a developed clustering rule, on two randomly generated scenarios for validation. The rule achieved reasonable order allocation to vehicles and reacted to different problem sizes by rejecting orders over the model capacity. This allocation shows a promising path in fully adopting the ABM model in this dynamic problem.