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1 INTRODUCTION
The laboriousness (complexity) of container handling
operations is usually evaluated by the average
number of moves required for their performing. In
order to calculate the commercial and operational
characteristics one also needs to consider the time
needed to implement each movement [1-4]. When the
analytical approach is used, one cannot think in terms
of single operations, so the mean time of moves is
usually considered instead. Still, the number of moves
is not deterministic but stochastic value and should be
described by distribution functions. In order to get
ones, e.g. distribution density, which is important
parameter for container terminal design and
operational management, usually methods of Monte-
Carlo group are used [5]. These methods, actually, can
be considered as an attempt to introduce individual
values of different parameters which are defined by
the integral functions of each characteristic. In a way,
these methods of random generation of values are
directly reversed to the generalization provided the
step before.
In many cases this approach can be considered as
oversimplified, i.e. when a terminal exploits several
different types of container handling equipment for
stacking operations. Another problem appears when
Planning Simulation Experiments in the Tasks of
Studying the Operational Strategies of Container
Terminals
A.L. Kuznetsov, A.V. Kirichenko & A.D. Semyonov
Admiral Makarov State University of Maritime and Inland Shipping, Saint-Petersburg, Russia
H. Oja
Konecranes Finland Corp., Hyvinkää, Finland
ABSTRACT: There is a lot of scientific papers that consider the efficiency of different container yard’s handling
strategies. The methods of assessment vary from abstract mathematical calculations to aposterioric collection
and analyses of practical data. This article deals with a new way of stacking strategy’s estimation. It postulates
that investigations based on the extrapolation of existing strategies cannot be reliable due to rapid changes in
terminals’ environment and restricted amount of data that can be collected within limited periods of the
strategies’ application. The hypothesis of the study is that the only method that could provide robust
comparative study of container stacking strategies is the simulation modelling. In the same time, any model is
only a tool of analyses. The synthesis could be provided only by massive iterations of single simulation
experiments with controlled searching procedure in the space of parameters. Consequently, the stress of the
simulation study should be put not on the model itself, but on the way how to use it, i.e. on the experiments
planning. Only a rationally constructed machine of simulation scenario generation could provide adequate and
statistically reliable results. In order to demonstrate the importance of this ‘task setting’ machine, two example
strategies are selected for comparison: (1) allocation of containers to slots with the minimum height and (2)
stacking of containers in accordance with expected dwell time. It also shows that the objective function has a
great impact on the optimal strategy implementation. In the study described in the paper the number of moves
requested to select a container is opted as an optimization criterion.
http://www.transnav.eu
the International Journal
on Marine Navigation
and Safety of Sea Transportation
Volume 14
Number 4
December 2020
DOI: 10.12716/1001.14.04.08