TY - JOUR
T1 - Managing Customer Arrivals with Time Windows
T2 - A Case of Truck Arrivals at a Congested Container Terminal
AU - Chen, Gang
AU - Jiang, Liping
PY - 2016
Y1 - 2016
N2 - Due to increasing container traffic and mega-ships, many seaports face challenges of huge amounts of truck arrivals and congestion problem at terminal gates, which affect port efficiency and generate serious air pollution. To solve this congestion problem, we propose a solution of managing truck arrivals with time windows based on the truck-vessel service relationship, specifically trucks delivering containers for the same vessel share one common time window. Time windows can be optimized with different strategies. In this paper, we first propose a framework for installing this solution in a terminal system, and second develop an optimization model for scaling time windows with three alternative strategies: namely fixed ending-point strategy (FEP), variable end-point strategy and greedy algorithm strategy. Third, to compare the strategies in terms of effectiveness, numerical experiments are conducted based on real data. The result shows that (1) good planning coordination is essential for the proposed method; and (2) FEP is found to be a better strategy than the other two.
AB - Due to increasing container traffic and mega-ships, many seaports face challenges of huge amounts of truck arrivals and congestion problem at terminal gates, which affect port efficiency and generate serious air pollution. To solve this congestion problem, we propose a solution of managing truck arrivals with time windows based on the truck-vessel service relationship, specifically trucks delivering containers for the same vessel share one common time window. Time windows can be optimized with different strategies. In this paper, we first propose a framework for installing this solution in a terminal system, and second develop an optimization model for scaling time windows with three alternative strategies: namely fixed ending-point strategy (FEP), variable end-point strategy and greedy algorithm strategy. Third, to compare the strategies in terms of effectiveness, numerical experiments are conducted based on real data. The result shows that (1) good planning coordination is essential for the proposed method; and (2) FEP is found to be a better strategy than the other two.
KW - Container terminal operations
KW - Gate congestion
KW - Truck arrivals
KW - Time window
KW - Optimization
KW - Container terminal operations
KW - Gate congestion
KW - Truck arrivals
KW - Time window
KW - Optimization
U2 - 10.1007/s10479-016-2150-3
DO - 10.1007/s10479-016-2150-3
M3 - Journal article
SN - 0254-5330
VL - 244
SP - 349
EP - 365
JO - Annals of Operations Research
JF - Annals of Operations Research
IS - 2
ER -