Journal of System Simulation
Abstract
Abstract: Aiming at the time-dependent vehicle routing problem with multiple time windows (TD_VRPMTW) that considers urban traffic congestion, a hybrid discrete gray wolf optimizer (HDGWO) is proposed. In the HDGWO, a new grey wolf individual updating formula is designed, and the integer coding method based on customer permutation is adopted, so that the algorithm can directly perform the global search based on GWO individual updating mechanism in the discrete problem solution space.A population initialization strategy based on the nature of the problem is designed to generate the initial population with high quality and diversity.The information exchange formula of the head wolf is introduced to explore the high-quality solution space formed by the head wolf. An adaptive variable neighborhood local search strategy with multiple local search operators is constructed to enhance the local search ability of the algorithm. Results show that HDGWO can effectively solve TD_VRPMTW.
Recommended Citation
Li, Nan; Hu, Rong; Qian, Bin; Jin, Huaiping; and Yu, Naikang
(2022)
"Research on Time-dependent Vehicle Routing Problem with Multiple Time Windows,"
Journal of System Simulation: Vol. 34:
Iss.
8, Article 11.
DOI: 10.16182/j.issn1004731x.joss.21-0244
Available at:
https://dc-china-simulation.researchcommons.org/journal/vol34/iss8/11
First Page
1775
Revised Date
2021-06-06
DOI Link
https://doi.org/10.16182/j.issn1004731x.joss.21-0244
Last Page
1788
CLC
TP391.9
Recommended Citation
Nan Li, Rong Hu, Bin Qian, Huaiping Jin, Naikang Yu. Research on Time-dependent Vehicle Routing Problem with Multiple Time Windows[J]. Journal of System Simulation, 2022, 34(8): 1775-1788.
DOI
10.16182/j.issn1004731x.joss.21-0244
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