Load scheduling for multiple quay cranes in port container terminals

Journal of Intelligent Manufacturing (Impact Factor: 1.14). 07/2006; 17(4):479-492. DOI: 10.1007/s10845-005-0020-y

ABSTRACT This paper proposes a method to schedule loading operations when multiple yard cranes are operating in the same block. The
loading scheduling methods in this paper are based on a genetic algorithm and a simulated annealing method, which consider
interferences between adjacent yard cranes. It attempts to minimize the make-span of the yard crane operation. We consider
the container handling time, the yard crane travel time, and the waiting time of each yard crane, when evaluating the makespan
of the loading operation by yard cranes. An encoding method considering the special properties of the optimal solution of
the problem is suggested. Numerical experiment was conducted to compare performances of the algorithms suggested in this study.

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    • "Due to the problem complexity, MIP models were commonly employed just to formulate yard related problems while heuristic methods were proposed to find near-optimal solutions. Jung and Kim (2006) considered 2 YCs working in one shared zone to support vessels loadings with a GA and a Simulated Annealing (SA) algorithm to minimize the makespan, i.e. the period between the starting time of the first YC operation and the finishing time of the last YC operation. Lee et al. (2007) considered 2 YCs working in 2 non-overlapping zones with a SA algorithm to minimize the makespan. "
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    ABSTRACT: Yard crane (YC) dispatching in the operational planning of container terminals usually aims to minimize makespan of YC operations or waiting time of vehicles. We propose that minimizing the maximum tardiness of vehicle jobs at yard blocks will minimize the operational delay of the longest quay crane (QC). This will minimize vessel turnaround time which is one of the most important objectives of container terminals. A provably optimal algorithm, MMT-RBA* to minimize maximum job tardiness, is presented to sequence the YC jobs. Jobs requiring reshuffling of other containers, often ignored in other studies, are handled by embedded simulation in our optimization algorithms. Another provably optimal algorithm, MMS-RBA* to minimize makespan, is also presented. Simulation experiments confirm that MMT-RBA* significantly outperforms the optimal algorithm RBA* to minimize vehicle waiting time from earlier studies and MMS-RBA* to minimize makespan in minimizing vessel turnaround time.
    Winter Simulation Conference 2014; 12/2014
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    • "The algorithms based on genetic algorithm and simulated annealing approaches were proposed to schedule the travelling route of the yard cranes and number of containers to pick up in each yard bay. Jung et al. (2006) extended the problem to schedule the loading sequence of the quay cranes considering the interference of multiple yard cranes. A greedy randomized adaptive search procedure was proposed for constructing a schedule to minimize the makespan of the quay cranes. "
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    ABSTRACT: With advancements of quay side equipments and technologies, the bottleneck of port operations has moved from quay side to yard side. The yard management of a port has significant influences on the competitiveness of a port in the global shipping network. The research area of yard management has attracted a lot of attentions from both the academia and the industrial practitioners. This paper gives a comprehensive review for the studies on the yard management in container terminals. From three aspects, i.e., yard cranes management, yard vehicles management, and yard spaces management, this paper reports the advances in these three areas. Some future directions on the yard management researches are also discussed. The purpose of this paper is to stimulate more practically relevant researches in this emerging area.
    12/2013; 12(4). DOI:10.7232/iems.2013.12.4.289
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    • "Given the deadlines of the vehicle jobs and their predicted arrival times at the yard block, the YC dispatching algorithm that computes its serving sequence to minimize the average (total) job tardiness will be more effective in reducing vessel turnaround time. When designing a YC dispatching algorithm, many previous work assumes that the YC service times for vehicle jobs are constant (Cao et al. 2008; Jung and Kim 2006; Lee et al. 2006 Guo et al. 2011). This is correct when the container to be retrieved/stored is on the top of the container stack in the yard. "
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    ABSTRACT: Two optimal algorithms, MTA* and MT-RBA*, are presented to find the optimal yard crane (YC) job sequence for serving a fleet of vehicles for delivery and pickup jobs with scheduled deadlines and predicted vehicle arrival times. The objective is to minimize the total tardiness of incoming vehicle jobs. This is important for minimizing vessel turnaround time. In the search for an optimal job sequence, the evaluation of the total tardiness of (partial) job sequences requires sequence dependent job service times. Simulation is embedded in our optimization algorithms to help provide accurate YC service times. This results in a more accurate evaluation of job tardiness but incurs costs. Experimental results show that this is feasible despite the simulation costs. MTA* and MT-RBA* significantly outperform the Earliest Due Date First and the Smallest Completion time Job First heuristics in minimizing job tardiness. MT-RBA* is computationally more efficient.
    The 2012 Winter Simulation Conference; 12/2012
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