Load scheduling for multiple quay cranes in port container terminals

Journal of Intelligent Manufacturing (Impact Factor: 1.28). 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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    ABSTRACT: Embedding simulation in optimization algorithms will incur computational costs. For NP-hard problems the computational costs of the embedded simulation in the optimization algorithm are likely to be substantial. YC dispatching is NP-hard. So it is very important to be able to minimize simulation costs in YC dispatching algorithms. In the optimization algorithm for yard crane dispatching published, simulation of YC operations of the entire (partial) sequence of YC jobs are carried out each time the tardiness of a (partial) sequence needs to be evaluated. In this paper we study two approaches to reduce simulation costs in these embedded simulations in the optimization algorithm. Experimental results show that one approach significantly reduces the computational time of the optimization algorithm. We also analyze the reasons for the other approach which fails to reduce the computational time.
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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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    ABSTRACT: One of the most important objectives in operation planning of a container terminal is to minimize vessel turnaround time. This means the vehicles have to reach the quay cranes such that they minimize the quay crane waiting time for them. This in turn means when vehicles go to yard blocks, they have deadlines for their loading/unloading jobs. The yard cranes should try to finish the vehicle jobs with minimal tardiness. The Apparent Tardiness Cost (ATC)-based dispatching rules are known to efficiently reduce tardiness for many scheduling problems. The ATCRSS dispatching rule is very effective in minimizing tardiness for single machines with sequence de-pendent setup and future ready time. The scaling parameters play an important role in the qual-ity of the solutions found by ATCRSS. We adapt this rule in yard crane dispatching where the job service time is also sequence dependent. We propose using Tabu search to find the best val-ues for the scaling parameters. We embed simulation to find the sequence dependent job service time. The performance of the adapted algorithm is evaluated against an optimal yard crane dis-patching algorithm. The performance of the adapted algorithm with the grid method for finding the scaling parameters is also tested.
    The 2013 International Conference on Logistics and Maritime Systems; 09/2013