Volume 55, 2021Regular articles published in advance of the transition of the journal to Subscribe to Open (S2O). Free supplement sponsored by the Fonds National pour la Science Ouverte
|Page(s)||S625 - S646|
|Published online||02 March 2021|
A bi-objective model for robust local container drayage problem
Department of Industrial Engineering, Tsinghua University, Beijing 100084, PR China
2 Logistics Engineering and Simulation Laboratory, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, PR China
3 Department of Transportation Engineering, College of Civil Engineering, Shenzhen University, Shenzhen 518060, PR China
4 School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China
* Corresponding author: firstname.lastname@example.org
Accepted: 12 July 2019
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.
Mathematics Subject Classification: 90B06
Key words: Local Container Drayage Problem / (un)packing time uncertainties / time buffer insertion / Ant Colony Optimization / Zoutendijk feasible direction algorithm
© EDP Sciences, ROADEF, SMAI 2021
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