Abstract
This paper examines the yard truck scheduling, the yard location assignment for discharging containers, and the quay crane scheduling in container terminals. Taking into account the practical situation, we paid special attention to the loading and discharging precedence relationships between containers in the quay crane operations. A Mixed Integer Program (MIP) model is constructed, and a two-stage heuristic algorithm is proposed. In the first stage an Ant Colony Optimization (ACO) algorithm is employed to generate the yard location assignment for discharging containers. In the second stage, the integration of the yard truck scheduling and the quay crane scheduling is a flexible job shop problem, and an efficient greedy algorithm and a local search algorithm are proposed. Extensive numerical experiments are conducted to test the performance of the proposed algorithms.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 21-37 |
| Number of pages | 17 |
| Journal | Journal of Systems Science and Systems Engineering |
| Volume | 22 |
| Issue number | 1 |
| DOIs | |
| State | Published - 2013 |
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Keywords
- ant colony optimization
- Container terminal
- precedence constraints
- quay crane scheduling
- yard location assignment
- yard truck scheduling
ASJC Scopus subject areas
- Information Systems
- Control and Systems Engineering
Cite this
An ant colony algorithm for yard truck scheduling and yard location assignment problems with precedence constraints. / Xue, Zhaojie; Zhang, Canrong; Miao, Lixin; Lin, Wei Hua.
In: Journal of Systems Science and Systems Engineering, Vol. 22, No. 1, 2013, p. 21-37.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An ant colony algorithm for yard truck scheduling and yard location assignment problems with precedence constraints
AU - Xue, Zhaojie
AU - Zhang, Canrong
AU - Miao, Lixin
AU - Lin, Wei Hua
PY - 2013
Y1 - 2013
N2 - This paper examines the yard truck scheduling, the yard location assignment for discharging containers, and the quay crane scheduling in container terminals. Taking into account the practical situation, we paid special attention to the loading and discharging precedence relationships between containers in the quay crane operations. A Mixed Integer Program (MIP) model is constructed, and a two-stage heuristic algorithm is proposed. In the first stage an Ant Colony Optimization (ACO) algorithm is employed to generate the yard location assignment for discharging containers. In the second stage, the integration of the yard truck scheduling and the quay crane scheduling is a flexible job shop problem, and an efficient greedy algorithm and a local search algorithm are proposed. Extensive numerical experiments are conducted to test the performance of the proposed algorithms.
AB - This paper examines the yard truck scheduling, the yard location assignment for discharging containers, and the quay crane scheduling in container terminals. Taking into account the practical situation, we paid special attention to the loading and discharging precedence relationships between containers in the quay crane operations. A Mixed Integer Program (MIP) model is constructed, and a two-stage heuristic algorithm is proposed. In the first stage an Ant Colony Optimization (ACO) algorithm is employed to generate the yard location assignment for discharging containers. In the second stage, the integration of the yard truck scheduling and the quay crane scheduling is a flexible job shop problem, and an efficient greedy algorithm and a local search algorithm are proposed. Extensive numerical experiments are conducted to test the performance of the proposed algorithms.
KW - ant colony optimization
KW - Container terminal
KW - precedence constraints
KW - quay crane scheduling
KW - yard location assignment
KW - yard truck scheduling
UR - http://www.scopus.com/inward/record.url?scp=84875445965&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84875445965&partnerID=8YFLogxK
U2 - 10.1007/s11518-013-5210-0
DO - 10.1007/s11518-013-5210-0
M3 - Article
AN - SCOPUS:84875445965
VL - 22
SP - 21
EP - 37
JO - Journal of Systems Science and Systems Engineering
JF - Journal of Systems Science and Systems Engineering
SN - 1004-3756
IS - 1
ER -