A bi-objective model for robust local container drayage problem

You，Jintao1,2; Zhang，Canrong1,2; Xue，Zhaojie3; Miao，Lixin1,2; Ye，Bin4

2021

10.1051/ro/2019063

RAIRO-OPERATIONS RESEARCH   影响因子和分区

0399-0559

1290-3868

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.

(un)packing time uncertainties Ant Colony Optimization Local Container Drayage Problem Time buffer insertion Zoutendijk feasible direction algorithm

SCI ; EI

英语

其他

National Natural Science Foundation of China[71502112,71872092,71472108] ; Shenzhen Municipal Science and Technology Innovation Committee[JCYJ20170302144108956] ; Natural Science Foundation of SZU[000154]

Operations Research & Management Science

Operations Research & Management Science

WOS:000624288700013

EDP SCIENCES S A

20211010047443

Door to door service (freight) ; NP-hard ; Numerical methods ; Sales ; Scheduling ; Tractors (truck) ; Transfer cases (vehicles)

Heavy Duty Motor Vehicles:663.1 ; Management:912.2 ; Optimization Techniques:921.5 ; Numerical Methods:921.6

2-s2.0-85102086879

Scopus

1.Department of Industrial Engineering,Tsinghua University,Beijing,100084,China
2.Logistics Engineering and Simulation Laboratory,Graduate School at Shenzhen,Tsinghua University,Shenzhen,518055,China
3.Department of Transportation Engineering,College of Civil Engineering,Shenzhen University,Shenzhen,518060,China
4.School of Environmental Science and Engineering,Southern University of Science and Technology,Shenzhen,518055,China

You，Jintao,Zhang，Canrong,Xue，Zhaojie,et al. A bi-objective model for robust local container drayage problem[J]. RAIRO-OPERATIONS RESEARCH,2021,55:S625-S646.

You，Jintao,Zhang，Canrong,Xue，Zhaojie,Miao，Lixin,&Ye，Bin.(2021).A bi-objective model for robust local container drayage problem.RAIRO-OPERATIONS RESEARCH,55,S625-S646.

You，Jintao,et al."A bi-objective model for robust local container drayage problem".RAIRO-OPERATIONS RESEARCH 55(2021):S625-S646.