Container Terminals and Cargo Systems — PART 1: INTRODUCTION

Kap Hwan Kim · Hans-Otto Günther
Container terminals and terminal operations
1. Container traffic
Over the recent years, the use of containers for intercontinental maritime
transport has dramatically increased. Figure 1 exhibits the growth of world
container turnover. Starting with 50 million TEU (twenty feet equivalent unit)
in 1985 world container turnover has reached more than 350 million TEU in 2004.
A further continuous increase is expected in the upcoming years, especially
between Asia and Europe. Since their introduction in the 1960s containers
represent the standard unit-load concept for international freight.
Transhipment of containers between different parties in a supply chain involves
manufacturers producing goods for global use, freight forwarders, shipping
lines, transfer facilities, and customers. Container terminals primarily serve
as an interface between different modes of transportation, e.g. domestic rail
or truck transportation and deep sea maritime transport. As globally acting
industrial companies have considerably increased their production capacities in
Asian countries, the container traffic between Asia and the rest of the world
has steadily increased (cf. Wang (2005)). For instance, from 1990 to 1996 total
container traffic volume between Europe and Asia doubled, whereas in the same
period total container flow between Europe and the Americas went up by only 10%.
A few facts highlight the ever increasing importance of maritime container
transportation (cf. Brinkmann (2005), Lee and Cullinane (2005), and Steenken et
al. (2004)). Fig. 1 Development of world container turnover (Unit: million TEU)

visited on June 2, 2006)
* Since regular sea container services began 1961 with routes between the
East Coast of the United States and ports in Central and South America, the
fraction of container transportation in the world’s deep-sea cargo rose to more
than 60%. Some major maritime freight routes are even containerized up to 100%.
* The transportation capacity of the worldwide container fleet has almost
doubled during the past 10 years. At the same time, the transportation capacity
of a single vessel rose steeply, culminating in the recent generation of 10,000
TEU container vessels.
* While the worldwide gross national product increased from 1990 to 2003 by
about 50%, world container turnover tripled in the same period.
* In 1997 as much as 93.7% of the piece goods handled in the port of Hamburg
were packaged in containers.
As a consequence, the number and capacity of seaport container terminals
increased considerably, although investments for deep-sea terminals and the
related infrastructure expansions almost reach one billion EURO, as it is
reported from the latest deep-sea container terminal project at Wilhelmshafen,
Germany. At the same time, there is an ongoing trend in the development of
seaport container terminal configurations to use automated container handling
and transportation technology, particularly, in countries with high labour
costs. Hence, manually driven cranes are going to be replaced by automated ones
and often automated guided vehicles (AGVs) are used instead of manually perated
Driven by huge growth rates on major maritime container routes, competition
between container ports has considerably increased. Not only handling
capacities of container terminals worldwide got larger and larger. Moreover,
significant gains in productivity were achieved through advanced terminal
layouts, more efficient IT-support and improved logistics control software
systems, as well as automated transportation and handling equipment. For
instance, in the port of Singapore, container turnover per employee quintupled
from 1987 to 2001. In the scientific literature container terminal logistics
have received increasing interest. Many papers have been published dealing with
individual strategic, operational and control issues of seaport container
terminals. Recent overviews can be found in Vis and de Koster (2003), Steenken
et al. (2004), Murty et al. (2005), Kim (2005) as well as Günther and Kim
(2005). 2. Container terminal operations Although seaport container terminals
considerably differ in size, function, and geometrical layout, they principally
consist of the same sub-systems (see Figure 2). The ship operation or berthing
area is equipped with quay cranes for the loading and unloading of vessels.
Import as well as export containers are stocked in a yard which is divided into
a number of blocks. Special stack areas are reserved for reefer containers,
which need electrical supply for cooling, or to store hazardous goods. Separate
areas are used for empty containers. Some terminals employ sheds for stuffing
and stripping containers or for additional logistics services. The truck and
train operation area links the terminal to outside transportation systems. The
chain of operations for export containers can be described as follows (see
Figure 3). After arrival at the terminal by truck or train the container is
identified and registered with its major data (e.g. content, destination,
outbound vessel, shipping line), picked up by internal transportation equipment
and distributed to one of the storage blocks in the yard. The respective
storage location is given by row, bay, and tier within the block and is
assigned in real time upon arrival of the container in the terminal. To store a
container at the yard block, specific cranes or lifting vehicles are used.
Finally, after arrival of the designated vessel, the container is unloaded from
the yard block and transported to the berth where quay cranes load the
container onto the vessel at a pre-defined stacking position. The operations
necessary to handle an import container are performed in the reverse order.
Fig. 2 Operation areas of a seaport container terminal and flow of transports
(Source: Steenken et al. (2004), p. 6) Fig. 3 Transportation and handling chain
of a container (Source: Steenken et al. (2004), p. 13) Scheduling the huge
number of concurrent operations with all the different types of transportation
and handling equipment involved is an extremely complex task. In view of the
ever changing terminal conditions and the limited predictability of future
events and their timing, this control task has to be solved in real time.
Seaport container terminals greatly differ by the type of transportation and
handling equipment used. Regarding quay cranes, single or dual-trolley cranes
can be found. The latter employ an intermediate platform for buffering the
loaded or unloaded container. The most common types of yard cranes are
rail-mounted gantry (RMG) cranes, rubber-tired gantry (RTG) cranes, straddle
carriers, reach stackers, and chassis-based transporters. Of these types of
cranes only RMG cranes are suited for fully automated container handling.
Figure 4 exhibits the working principle of the different types of handling
equipment and their comparative performance figures with respect to the number
of TEUs, hich can be stored per hectare. Fig. 4 Different types of handling
equipment (Source:; visited on
January 2, 2006) Different types of vehicles can be used both for the
ship-to-yard transportation and the interface between the yard and the
hinterland. The most common types are multi-trailer systems (MTS) with manned
trucks, automated guided vehicles (AGVs), and automated lifting vehicles
(ALVs). The latter ones, in contrast to AGVs, are capable of lifting a
container from the ground by themselves (cf. Vis and Harika, 2004; Yang et al.,
2004). However, despite their superior handling capabilities ALVs have not yet
gained idespread use in container terminals. 3. Planning and logistics control
issues of container terminals A container terminal represents a complex system
with highly dynamic interactions between the various handling, transportation
and storage units, and incomplete knowledge about future events. There are many
decision problems related to logistics planning and control issues of seaport
container terminals. These problems can be assigned to three different levels
as shown in Figure 5: terminal design, operative planning, and real-time
control. In the following a brief overview of these planning and control levels
and their relationship to the various kinds of terminal equipment is given.
Terminal design problems have to be solved by facility planners in the initial
planning stage of the terminal. These problems have to be analyzed both from an
economic as well as a technical feasibility and performance point of view. In
particular, construction of a completely new terminal site and the use of
automated equipment require huge investments. From the various design problems,
only the most important ones shall be highlighted. For a more detailed overview
see Steenken et al. (2004).
* Multi-modal interfaces: In contrast to their Asian counterparts, most
European container terminals are laid out as multi-modal facilities, i.e. they
are directly linked to railway, truck and inland navigation systems. The
integration of these different modes of transportation has a major impact on
the design of the entire terminal. Fig. 5 Logistics planning and control issues
in seaport container terminals
* Terminal layout: The storage yard, transportation guide paths, and quays
represent the major entities of each container terminal. Their capacity and
spatial arrangement heavily determine the performance of the terminal
configuration. Terminal layout also includes the reservation of certain areas
for reefer or hazardous goods containers, empty сontainers or non-standard-size
* Equipment selection: Different types of equipment can be used for handling
and transportation within the terminal. They primarily differ by their degree
of automation and their performance figures. Currently, there is an ongoing
trend to make increased use of automated storage cranes und driverless
vehicles, although these types of equipment raise complex logistics control
* Berthing capacity: The global performance factor of a container terminal
is given by its seaside dispatching capacity. The berthing capacity not only
determines the number and size of the vessels that can be served, but also the
requirements for storage yard space and the fleet size of vehicles etc.
* IT-systems and control software: Finally, logistics control in large-sized
container terminals is a tremendously complex task, which requires real-time
decisions on matching handling tasks with the corresponding equipment units and
the provision of detailed information about each individual container.
Different modes of software and IT support as well as use of sophisticated
optimization tools are issues of considerable importance. The level of
operative planning (cf. Steenken et al. (2004)) comprises guidelines and basic
planning procedures for performing the various logistic processes at the
terminal. Since decentralized planning is the only realistic mode to govern
logistics control of automated container terminals, the entire logistics
control system is subdivided into various modules for the different types or
groups of resources. Hence, specific issues arise in planning and scheduling
the use of key resources for a short-term planning horizon of several days or
* Berth allocation: Before arrival of a ship, the required berthing space
has to be allocated taking the prospective time the ship spends in the terminal
into account. Additional constraints arise from the availability of cranes and
the berthing and crane requirements of other vessels which already moor at the
quay or are expected to arrive shortly.
* Crane assignment and split: To load and unload a large container vessel,
several quay cranes are used. First it has to be decided which individual
cranes are to be assigned to the various ships considering the accessibility of
cranes at the berth and the impossibility to exchange cranes between different
berths at the terminal. Second the cranes operating at one ship have to be
assigned to different sections or hatches of the ship.
* Stowage planning and sequencing: Shipping lines have to decide which
positions within the ship are assigned to specific categories of containers
considering container attributes such as destination, weight or type of the
container. Based on this given assignment, the terminal operator decides which
individual container has to be stored at the specific slots within the vessel.
This final slot-assignment heavily affects the loading and unloading sequence
of containers. Based on the stowage plan, planners in container terminals
determine the sequence of unloading inbound containers and of loading outbound
containers. For the outbound containers, in addition to the loading sequence
for individual containers, the slot in the vessel into which each outbound
container will be stacked must be determined at the same time. The unloading
and loading sequences represent a major input for determining the yard crane’s
and vehicle’s schedules
* Storage and stacking policies: Large container terminals in Europe store a
total of several 10,000 containers with average dwell times of 3-5 days and
daily turnover of 10-20,000 containers. The storage area is separated into
blocks, which are organized into bays, rows and tiers. Policies for assigning
individual storage locations and stacking of containers are ruled by the
objective to expedite the necessary storage and retrieval operations as far as
possible and to avoid reshuffling of containers within the block. Specific
issues include the reservation of dedicated storage areas for import and export
containers and the planning of remarshalling operations for stacked containers.
* Workforce scheduling: Workforce is another important resource in container
terminals. Rosters and schedules for workers to operate equipment must be
generated in advance. Container terminals represent highly dynamic and
highly stochastic logistics systems, which do not allow pre-planning of
detailed transportation and handling activities for a look-ahead horizon of
more than 5-10 minutes. Hence, real-time control of logistics activities is of
utmost importance. Real-time control (or realtime planning) is usually
triggered by certain events or conditions and requires that the underlying
decision problem is solved within a very short time span, in practice usually
within less than a second. Real-time decisions include the assignment of
transportation orders to vehicles and routing and scheduling the vehicle trips
for landside transportation as well as for transportation between the berth and
the storage yard, the assignment of storage slots to individual containers, and
the determination of detailed schedules and operation sequences for quay and
stacking cranes. 4. Overview of the book Apart from this introductory section,
this book is divided into two further Parts 2 and 3. The subsequent Part 2
focuses on seaport container terminals while the final Part 3 considers other
types of cargo systems, e.g. vehicle distribution, air and maritime cargo
systems as well as issues of revenue management and collaboration between
forwarding enterprises. Part 2 comprises eleven papers on seaport container
terminals. Due to the complexity of automated container terminals, highly
sophisticated control strategies are needed for the operation and control of
the equipment. In addition, the design and the performance analysis of terminal
configurations are issues of major practical importance. The first paper by
J.A. Ottjes, H.P.M. Veeke, M.B. Duinkerken, J.C. Rijsenbrij and G. Lodewijks
presents a generic simulation model structure for the design and evaluation of
multi-terminal systems. The authors apply their modelling approach to the
existing and the future terminals in the Rotterdam port area. Experimental
results show the requirements for deep-sea quay lengths, storage capacities,
and equipment for inter-terminal transport. A simulation study to compare
three different transportation systems for the overland transport of containers
between container terminals is presented in the paper by M.B. Duinkerken, R.
Dekker, S.T.G.L. Kurstjens, J.A. Ottjes and N.P. Dellaert. The simulation model
is applied to a realistic scenario taken from the Rotterdam port area. The
numerical results give insight into the different characteristics of the
transport systems and their interaction with the handling equipment. In the
subsequent paper, R. Moorthy and C.-P. Teo analyse the home berth problem, i.e.
the preferred berthing location for a set of vessels scheduled to call at the
container terminal on a weekly basis. They model this problem as a rectangular
packing problem on a cylinder and use a sequence pair based simulated annealing
algorithm to solve the problem. Extensive computational studies show the
efficiency of the proposed modelling approach. In their paper, E. Kozan and P.
Preston model the seaport terminal system with the objective of determining the
optimal storage strategy and container-handling schedule. They present an
iterative search algorithm that integrates a containertransfer with a container
location model in a cyclic fashion to determine both optimal locations and
corresponding handling schedules. Results are analysed and compared with
current practise at an Australian port. A mixed-integer linear programming
model for storage yard management in transhipment hubs is presented by L.H.
Lee, E.-P. Chew, K.C. Tan and Y. Han. To solve large-sized problem instances,
two heuristic solution procedures are developed. The first is a sequential
method while the second is based on column generation. Finally, it is shown
that the heuristics find near-optimal solutions in a reasonable amount of time.
Stacking policies for containers at an automated container terminal are
addressed by R. Dekker, P. Voogd and E. van Asperen. They provide a
comprehensive overview of stacking policies used in practise. Specifically,
they consider several variants of category stacking, where containers can be
exchanged during the loading process. In a numerical study, different stacking
policies are compared. The next paper by E.K. Bish, F.Y. Chen, Y.T. Leong,
B.L. Nelson, J.W.C. Ng and D. Simchi-Levi analyses discharging and uploading
operations of containers to and from ships. Specifically, the authors address
the dispatching of vehicles to containers so as to minimize the service time
(makespan) of a ship. To solve this problem they develop heuristic dispatching
algorithms that generate optimal or near-optimal solutions. In the paper by M.
Grunow, H.-O. Günther and M. Lehmann strategies for dispatching Automated
Guided Vehicles (AGVs) at automated seaport container terminals are analysed
and evaluated using a scalable simulation model. The authors develop a
so-called pattern-based heuristic which utilizes the dual-load capability of
AGVs. Results of the simulation study reveal that this heuristic outperforms
conventional dispatching heuristics known from flexible manufacturing systems.
Another type of dispatching strategies for AGVs is proposed by D. Briskorn, A.
Drexl and S. Hartmann. They present an alternative formulation of the
jobvehicle assignment problem which is based on a rough analogy to inventory
management. In a simulation study, it is shown that the inventory-based model
leads to better productivity of the terminal than the due-time-based model
formulation. In automated container terminals, situations occur where
different equipment units directly or indirectly request each other to start a
specific process. Hence, all of the affected resources are involved in a
deadlock. M. Lehmann, M. Grunow and H.-O. Günther develop different methods for
the detection and resolution of deadlocks occurring in the resource-assignment
phase. The suitability of these methods is shown in a comprehensive simulation
study. Another type of deadlocks arising in the traffic control of AGVs in
seaport container terminals is investigated by K.-H. Kim, S.M. Jeon and K.R.
Ryu. They develop an efficient deadlock rediction and prevention algorithm
Their approach guarantees deadlock-free reservation schedules of grid blocks in
the guide path for AGVs to cross the same area at the same time. The proposed
method was tested in a simulation study. Part 3 comprises six papers on
different types of cargo systems. The first paper by D.C. Mattfeld and H. Orth
addresses the planning of transportation and storage capacity over time. They
consider intermodal transhipment terminals used for the import and export of
large volumes of automotives and develop an evolutionary algorithm for
determining a period-oriented capacity utilization strategy. As a result, a
balanced distribution of vehicle movements over the periods of the planning
horizon is achieved. The next paper by H. C. Huang, C. Lee and Z. Xu considers
a large air cargo handling facility composed of two identical cargo terminals.
To balance the workload between the two terminals, a stochastic mixed-integer
linear programming model is developed and efficiently solved. The simulation
results based on data from a large international air port show that the
proposed algorithms effectively balance the workload and the cargo service time
is considerably reduced. In their paper, D. Li, H.-C. Huang, A.D. Morton and
E.-P. Chew develop an integrated model for incorporating the cargo routing
problem into fleet assignment. Their solution approach is based on Benders
decomposition and simultaneously determines the optimal assignment of fleets
(types of airplanes) to flight-legs and the routing of cargo over the network
within reasonable amount of computational time. A mathematical programming
based approach for revenue management in cargo airlines is the topic of the
paper by P. Bartodziej, U. Derigs and M. Zils. Their approach deals with making
capacity reservations for expected cargo demand over a certain period of time,
e.g. a year, so as to maximize the expected profit contribution. As the number
of booking request per week for a major cargo airline is extremely large, an
issue of considerable practical importance is to answer customer enquiries in
near real-time. The paper by L.H. Lee, E.-P. Chew and M.S. Sin also deals with
issues of revenue management. They show that, in a sea cargo application, the
optimal policy to allocate the capacity of a ship is a threshold policy, i.e.
to base decisions on the acceptance of customer orders on the remaining
capacity of the ship. An efficient heuristic procedure is proposed to solve
this problem. The final paper by M.A. Krajewska and H. Kopfer presents a model
for collaboration among independent freight forwarding enterprises. Their model
is based on theoretical foundations of combinatorial auctions and game theory.
They show that through their collaboration model additional profit for a
coalition of freight forwarders and for each participant can be gained.
Therefore, the proposed model provides a useful basis for developing
application-specific profit sharing mechanisms in the freight forwarding
business. 5. Final remarks The primary objective of this book is to reflect
recent developments in design, operations management and logistics control of
automated container terminals and cargo systems and to examine related research
issues of quantitative analysis and decision support. It comprises reports on
the state of the art, applications of quantitative methods, as well as case
studies and simulation results. Seventeen papers previously published in “OR
Spectrum – Quantitative Approaches in Management” have been selected for
publication in this volume. All papers have been peer-reviewed according to the
standards of the journal. This book has greatly benefited from the cooperation
among the authors, reviewers, and editors. We would like to express our sincere
thanks to the reviewers for their excellent and timely refereeing. Last, but
not least, we thank all the authors for their contributions which made this
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