A simulation-based Genetic Algorithm approach for the quay crane scheduling under uncertainty

被引:53
作者
Al-Dhaheri, Noura [1 ]
Jebali, Aida [1 ]
Diabat, Ali [1 ]
机构
[1] Masdar Inst Sci & Technol, Dept Engn Syst & Management, Abu Dhabi, U Arab Emirates
关键词
Quay Crane scheduling; Straddle carriers; Stochastic programming; Simulation-based Genetic Algorithm; OPTIMIZATION; ASSIGNMENT; OPERATIONS; BRANCH; BERTH; TIME;
D O I
10.1016/j.simpat.2016.01.009
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The fast-paced growth in containerized trade market sparks the need for efficient operations at seaport container terminals. One major determinant of terminal efficiency is the productivity of Quay Cranes (QC) resulting from QC scheduling. This paper focuses on the QC Scheduling Problem (QCSP). The objective is to minimize vessel handling time while considering the entire container handling process involving both seaside operations and container transfer operations, taking place between the quay and the stacking yard. A stochastic mixed integer programming model is proposed, and a simulation-based Genetic Algorithm (GA) is applied to construct QC schedules that account for the dynamics and the uncertainty inherent to container handling process. Computational experiment shows satisfactory results of the proposed algorithm and stresses the importance of simulation to obtain more reliable estimates of QC schedule performance. (C) 2016 Elsevier B.V. All rights reserved.
引用
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页码:122 / 138
页数:17
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