Multi-Depot Split-Delivery Vehicle Routing Problem

The rapid advancements in information technologies and globalization change the way of distributing goods to customers. Many enterprises have multiple factories, warehouses, and distribution centers and strive for competitive efficiency in the distribution operations to minimize transportation costs. This study proposed the mixed-integer programming (MIP) model for the multi-depot split-delivery vehicle routing problems (MDSDVRPs) with hetero vehicles, allowing multiple visits to a customer. A genetic algorithm (GA) with a novel two-dimensional chromosome representation has been proposed with dynamic mutation policies. The process parameters of the proposed GA are optimized using the Taguchi method. The proposed algorithms showed the benefits of split-delivery in MDSDVRPs and showed the competitive performance even for the classical single-depot vehicle routing problems with no split-delivery.

Automated summary

This study proposed a mixed-integer programming model and a genetic algorithm for the multi-depot split-delivery vehicle routing problems, showing the benefits and competitive performance of the algorithms through optimized process parameters. The results of the study suggest that split-delivery has positive implications for reducing transportation costs.