© 2019 Elsevier B.V.The time-dependent vehicle routing problem with time windows (TDVRPTW) is examined in this study. A mathematical model for the TDVRPTW is formulated by considering the time-dependent vehicle speeds, capacity, travel time, wait time, customer demand, service time, time window, impact of dynamic loads, and travel speed effect on vehicle carbon emissions. The objective of the TDVRPTW model is to minimize the sum of the fixed costs of the vehicle used, as well as the costs of drivers, fuel consumption, and carbon emissions. A calculation method for the road travel time across time periods with time-dependent speeds is presented. A congestion avoidance approach is proposed to avoid peak hour traffic congestion and temporal traffic congestion. An improved ant colony algorithm with a congestion avoiding approach (IACACAA) is elucidated according to the characteristics of the TDVRPTW model. The effectiveness of the proposed approaches was demonstrated in several computational experiments. The results show that the proposed IACACAA can scientifically plan the departure time and driving route for each vehicle, effectively avoid traffic congestion, and reduce the total distribution costs. The congestion avoidance approach effectively reduces vehicle fuel consumption and carbon emissions and protects the environment.
https://doi.org/10.1016/j.knosys.2019.06.021Cite as:
@article{Liu_2020,
doi = {10.1016/j.knosys.2019.06.021},
url = {https://doi.org/10.1016%2Fj.knosys.2019.06.021},
year = 2020,
month = {jan},
publisher = {Elsevier {BV}},
volume = {188},
pages = {104813},
author = {Changshi Liu and Gang Kou and Xiancheng Zhou and Yi Peng and Huyi Sheng and Fawaz E. Alsaadi},
title = {Time-dependent vehicle routing problem with time windows of city logistics with a congestion avoidance approach},
journal = {Knowledge-Based Systems}
}