Local Container Drayage Problem (LCDP) refers to the optimization of the process of planning and scheduling container trucks between a terminal and customers to offer door-to-door service to customers in a local area. The time required for (un)packing containers at customers’ sites are often relatively long and uncertain due to the current (un)packing work level and unexpected deviations in operational situations, which has a significant influence on the planning and scheduling of the container transportation process. This paper examines the LCDP with Separable tractors and trailers, and additionally with consideration of (un)packing time Uncertainties (LCDPSU). A proactive strategy is employed to tackle the uncertainty by proposing a “model robust” bi-objective optimization model to balance the tradeoff between operational cost, which includes traveling cost and tractor deployment setup cost, and robustness, which is represented as an exponential expression of the time buffer between two stages of each individual task. The deterministic version of our problem is proved to be NP hard, and an Ant Colony Optimization (ACO) scheme is therefore proposed to search for feasible solutions in which the Zoutendijk feasible direction algorithm is embedded in order to tackle the nonlinearity brought in by the robustness of the model. Numerical experiments are conducted to validate the efficiencies and effectivenesses of the proposed models and methods, and managerial implications are drawn from the numerical results.
Keywords: Local Container Drayage Problem, (un)packing time uncertainties, time buffer insertion, Ant Colony Optimization, Zoutendijk feasible direction algorithm
@article{RO_2021__55_S1_S625_0,
author = {You, Jintao and Zhang, Canrong and Xue, Zhaojie and Miao, Lixin and Ye, Bin},
title = {A bi-objective model for robust local container drayage problem},
journal = {RAIRO. Operations Research},
pages = {S625--S646},
year = {2021},
publisher = {EDP-Sciences},
volume = {55},
doi = {10.1051/ro/2019063},
mrnumber = {4223097},
zbl = {1479.90040},
language = {en},
url = {https://www.numdam.org/articles/10.1051/ro/2019063/}
}
TY - JOUR AU - You, Jintao AU - Zhang, Canrong AU - Xue, Zhaojie AU - Miao, Lixin AU - Ye, Bin TI - A bi-objective model for robust local container drayage problem JO - RAIRO. Operations Research PY - 2021 SP - S625 EP - S646 VL - 55 PB - EDP-Sciences UR - https://www.numdam.org/articles/10.1051/ro/2019063/ DO - 10.1051/ro/2019063 LA - en ID - RO_2021__55_S1_S625_0 ER -
%0 Journal Article %A You, Jintao %A Zhang, Canrong %A Xue, Zhaojie %A Miao, Lixin %A Ye, Bin %T A bi-objective model for robust local container drayage problem %J RAIRO. Operations Research %D 2021 %P S625-S646 %V 55 %I EDP-Sciences %U https://www.numdam.org/articles/10.1051/ro/2019063/ %R 10.1051/ro/2019063 %G en %F RO_2021__55_S1_S625_0
You, Jintao; Zhang, Canrong; Xue, Zhaojie; Miao, Lixin; Ye, Bin. A bi-objective model for robust local container drayage problem. RAIRO. Operations Research, Tome 55 (2021), pp. S625-S646. doi: 10.1051/ro/2019063
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