# DMRVR: Dynamic Milk-Run Vehicle Routing Solution Using Fog-Based Vehicular Ad Hoc Networks
## 5 Conclusions  
The evidence from this study points towards the idea that the use of a vehicular network merged with fog computing contributes to provide a novel solution to the dynamic vehicle routing problem (DVRP) concerning milk-run operations. In the literature review, we did not find other studies proposing the use of VANET based application in milk run operations. The solution described in [10] only identifies the supplier's delay when the pickup vehicle is already at the supplier, generating unnecessary travel times. Our solution (DMRVR) allows the pickup vehicles and the logistics operator to maintain updated information about the suppliers and the vehicle positions by using the vehicular network. This feature enables faster and more accurate decision-making, avoiding possible losses for the OEM. Different from [11], when DMRVR identifies that the pickup vehicle is behind schedule and is not going to make all the pickups, our solution removes suppliers from the route. Thus, the pickup vehicle immediately sends its new route to the  
Figure 8: Message delivery success rate. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
\begin{tabular}{c} **Vehicle** \\ **Density** \\ \end{tabular} & \multicolumn{2}{c}{**Success Rate**} & \multicolumn{2}{c}{**End-to-End**} & \multicolumn{2}{c}{**Max. Transmission**} \\  & & \multicolumn{2}{c}{**Delay**} & \multicolumn{2}{c}{**Distance**} \\  & **9 RSUs** & **11 RSUs** & **9 RSUs** & **11 RSUs** & **9 RSUs** & **11 RSUs** \\ \hline
600 & 45.83\% & 62.50\% & 0.012 s & 22.14 s & 9385 m & 9719 m \\
1200 & 62.50\% & 83.33\% & 0.060 s & 16.22 s & 9475 m & 9725 m \\
3900 & 79.17\% & 83.33\% & 0.020 s & 8.35 s & 9753 m & 9726 m \\
4600 & 83.33\% & 87.50\% & 0.022 s & 21.54 s & 9777 m & 9725 m \\ \hline \hline \end{tabular}
\end{table} 
Table 9: Vehicular network impacts. logistics operator. This approach allows the auxiliary pickup vehicle to start its displacement as soon as possible within the JIT limit imposed by the OEM. In our simulated-based experiments, the real-time communication between the logistics operator and the vehicles allowed delays (from the suppliers or traffic jams) to be analyzed in time to make changes to the route. We noticed that, in sparse scenarios (lower density of vehicles), the addition of RSUs increased the message delivery rate; however, some messages were lost, which can negatively affect the OEM supply chain. Due to the simulation model size, one of the main limitations of this work was the processing time. In the most representative scenario with a peak density of 4600 vehicles, the simulation time averaged 195 h. Any change in the model or execution of new algorithms became too time-consuming. Further experimental investigations are needed to analyze the dynamic vehicle routing considering different types of milk-run operations, supplier numbers and locations, addition, and removal of suppliers from the route. Future work should focus on enhancing the message delivery reliability. We also suggest developing a new mechanism to identify the most optimized RSU distribution. Finally, our results are promising, and other VANET-based logistics applications should use DMRVR. Conceptualization, D.D.A., A.G.N.N. and M.W. ; methodology D.D.A. and M.W. ; experiments, simulation and writing--original draft preparation, D.D.A., M.W. ; supervision, writing--review and technical review, A.G.N.N., C.M. and M.W. All authors have read and agreed to the published version of the manuscript. This work was partially supported by by Fundancao de Amparo a Pesquisa do Estado de Santa Catarina (FAPESC)--Grant 2019 TR169, in part by the Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior - Brazil (CAPES) - Finance Code 001, by Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPq)--Grant 302412/2016-6, and by CAPES under the project Print CAPES-UFSC \"Automation 4.0\". Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the funding agencies.