D. Satyananda, A. Abdullah
This paper reviews the implementation design of Deep Learning in Vehicle Routing Problem. Congestion and traffic condition are usually avoided in Vehicle Routing Problem due to its modeling complexity, and even the benchmark datasets only cover essential conditions. In the real situation, the traffic condition is varied, and congestion is the worst part. To model the real life, the delivery route must consider these situations. The vehicle needs information on traffic prediction in future time to avoid congestion. The prediction needs historical traffic data, which is very large. Deep Learning can handle the enormous size and extract data features to infer the prediction. © 2021 Institute of Physics Publishing. All rights reserved.
School of Computing, Universiti Teknologi Malaysia, Johor, Skudai, 81310, Malaysia; Department of Mathematics, Universitas Negeri Malang, Jl. Semarang 5, Malang, 65145, Indonesia; Department of Mathematics, Universitas Negeri Malang, Jl. Semarang 5, Malang, 65145, Malaysia
