Vehicle routing is an important combinatorial optimization problem. In real transport networks,the travel speed and travel time of roads have large time-variability and randomness. The study of vehicle routing problem in time-dependent network has even more practical value than static network VRP problem. This paper combines the features of time-dependent networks and gives the mathematical models of the time-dependent vehicle routing problem. On this basis, the traditional ant colony optimization algorithm is improved. A new path transfer strategy of ants and new dynamic pheromone update strategy applicable to time-dependent network are proposed. Based on these strategies, the improved ant colony algorithm is given for solving the vehicle routing problem in time-dependent networks. The simulation results show that the algorithm can effectively solve the vehicle routing problem in time-dependent network and has better computational efficiency and convergence speed.
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Copy
Yongqiang LIU, Qing CHANG, Huagang XIONG, "An Improved Ant Colony Algorithm for the Vehicle Routing Problem in Time-Dependent Networks" in IEICE TRANSACTIONS on Communications,
vol. E94-B, no. 5, pp. 1506-1510, May 2011, doi: 10.1587/transcom.E94.B.1506.
Abstract: Vehicle routing is an important combinatorial optimization problem. In real transport networks,the travel speed and travel time of roads have large time-variability and randomness. The study of vehicle routing problem in time-dependent network has even more practical value than static network VRP problem. This paper combines the features of time-dependent networks and gives the mathematical models of the time-dependent vehicle routing problem. On this basis, the traditional ant colony optimization algorithm is improved. A new path transfer strategy of ants and new dynamic pheromone update strategy applicable to time-dependent network are proposed. Based on these strategies, the improved ant colony algorithm is given for solving the vehicle routing problem in time-dependent networks. The simulation results show that the algorithm can effectively solve the vehicle routing problem in time-dependent network and has better computational efficiency and convergence speed.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E94.B.1506/_p
Copy
@ARTICLE{e94-b_5_1506,
author={Yongqiang LIU, Qing CHANG, Huagang XIONG, },
journal={IEICE TRANSACTIONS on Communications},
title={An Improved Ant Colony Algorithm for the Vehicle Routing Problem in Time-Dependent Networks},
year={2011},
volume={E94-B},
number={5},
pages={1506-1510},
abstract={Vehicle routing is an important combinatorial optimization problem. In real transport networks,the travel speed and travel time of roads have large time-variability and randomness. The study of vehicle routing problem in time-dependent network has even more practical value than static network VRP problem. This paper combines the features of time-dependent networks and gives the mathematical models of the time-dependent vehicle routing problem. On this basis, the traditional ant colony optimization algorithm is improved. A new path transfer strategy of ants and new dynamic pheromone update strategy applicable to time-dependent network are proposed. Based on these strategies, the improved ant colony algorithm is given for solving the vehicle routing problem in time-dependent networks. The simulation results show that the algorithm can effectively solve the vehicle routing problem in time-dependent network and has better computational efficiency and convergence speed.},
keywords={},
doi={10.1587/transcom.E94.B.1506},
ISSN={1745-1345},
month={May},}
Copy
TY - JOUR
TI - An Improved Ant Colony Algorithm for the Vehicle Routing Problem in Time-Dependent Networks
T2 - IEICE TRANSACTIONS on Communications
SP - 1506
EP - 1510
AU - Yongqiang LIU
AU - Qing CHANG
AU - Huagang XIONG
PY - 2011
DO - 10.1587/transcom.E94.B.1506
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E94-B
IS - 5
JA - IEICE TRANSACTIONS on Communications
Y1 - May 2011
AB - Vehicle routing is an important combinatorial optimization problem. In real transport networks,the travel speed and travel time of roads have large time-variability and randomness. The study of vehicle routing problem in time-dependent network has even more practical value than static network VRP problem. This paper combines the features of time-dependent networks and gives the mathematical models of the time-dependent vehicle routing problem. On this basis, the traditional ant colony optimization algorithm is improved. A new path transfer strategy of ants and new dynamic pheromone update strategy applicable to time-dependent network are proposed. Based on these strategies, the improved ant colony algorithm is given for solving the vehicle routing problem in time-dependent networks. The simulation results show that the algorithm can effectively solve the vehicle routing problem in time-dependent network and has better computational efficiency and convergence speed.
ER -