Today, reducing fossil fuel consumption in the transport sector is one of the important requirements to preserve the ecological environment.
The research group of the faculty of Electronics and Automation in
We conducted a numerical analysis on fuel consumption minimizing path selection between two customer nodes and found that the path selection is independent of the payload in most cases.
The model is formulated as a mathematical integer linear programming model, and small problems are solved using a commercial optimization solver.
For the large-scale instances, we proposed a heuristic algorithm based on the variable neighborhood search and evaluated its performance. The proposed algorithm can decrease fuel consumption by 25 % compared to manual routing and scheduling.
The result has been published in "Cleaner Logistics and Supply Chain" in 2024 under the title of "A practical vehicle routing problem in small and medium cities for fuel consumption minimization" (https://doi.org/10.1016/j.clscn.2024.100164).
