Defining an intermodal container distribution network: a generic understanding and selection procedure; Het definiëren van een intermodaal container distributie netwerk: een generiek inzicht en selectieprocedure

Delft University of Technology

FACULTY MECHANICAL, MARITIME AND MATERIALS ENGINEERING

Department Maritime and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl

This report consists of 45 pages and 1 appendix. It may only be reproduced literally and as a whole. For commercial purposes only with written authorization of Delft University of Technology. Requests for consult are only taken into consideration under the condition that the applicant denies all legal rights on liabilities concerning

Specialization: Transport Engineering and Logistics

Report number: 2014.TEL.7832

Title:

Defining an intermodal container

distribution network: a generic

understanding and selection

procedure

Author:

W.A. de Kluijver

Title (in Dutch) Het definiëren van een intermodaal container distributie netwerk: een generiek inzicht en selectieprocedure

Assignment: Literature Assignment

Confidential: No

Initiator (university): Dr. R.R. Negenborn Initiator (company): -

Supervisor: L. Li and Dr. R.R. Negenborn

Delft University of Technology

FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERING

Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl

Student: W.A. de Kluijver Assignment type: Literature assignment Supervisor (TUD): L. Li

Dr. R.R. Negenborn

Creditpoints (EC): 10

Supervisor (Company) - Specialization: TEL

Report number: 2014.TEL.7832 Confidential: No

Subject: Defining an intermodal container distribution network: a generic understanding and selection procedure

As the volume of container transport grows, container fleet management becomes increasingly important, such as is clear in the Rhine-Meuse delta, which include the seaport of Rotterdam.

The container distribution system (over land) is composed of a number of port terminals, in-land depots, and customer locations. Ships arrive in ports carrying loaded and empty containers of various types and dimensions. Loaded containers are delivered to their destinations, using rail and truck, while empty containers are

available for delivery to customers in the vicinity of the port or for repositioning. Customers receiving loaded containers unload them and signal that they may be picked up and transported to a designated terminal (port or in-land). Similarly, customers that require empty containers of specific types for future shipments receive them from an in-land or a port terminal. It is the question which containers (loaded, but in particular also empty ones) should go where and when.

What makes this container distribution system in particular interesting is the presence of uncertainty: demands vary in time, the time required by customers to unload and return containers varies, containers may unexpectedly get damaged, and the actual travel time for transporting a container between two locations is subject to variation.

Models capturing these uncertainties and dynamics are required in order to better control the container flows.

In this literature assignment you investigate how to best model container distribution networks for container fleet management. You will hereby in particular focus on the situation in The Netherlands. In particular, you will address questions such as:

 What does a real life intermodal container distribution network look like? Which players are involved? What infrastructure is used?

 How could container distribution networks be modeled? What modeling approaches and networks can be found in literature?

 How could an intermodal network of terminals and connections be selected? What would such a network look like in the Netherlands?

It is expected that you conclude your computer assignment with a written report, including conclusions and recommendations for future research. The report must be written in English and must comply with the guidelines of the section. Details can be found on the website. For more information, contact Rudy Negenborn (8B-1-05; r.r.negenborn@tudelft.nl).

The supervisors,

Summary

A container distribution network can be seen as the extension of a port deep into the continent: the hinterland. Development of such a network, consisting of terminals and connections, is therefore crucial for the expansion of a port. Developing the network can be done by adding features to the network (‘system design’) or more effectively using the network (‘service network design’). For both design issues one can use a mathematical optimization problem to optimally upgrade the transport system or service. Issues like, determining the location of new terminals, the quantity of equipment to install, on what route to provide services and how to distribute the containers through a physical network, can be solved. The goal is to satisfy the customers in the most cost-efficient way. This transportation problem is the subject of many researches. However, models dealing with intermodal transportation are still limited and are in general based on merged unimodal transportation models. The intermodal networks are more extensive and therefore difficulties arise in solving these models, which are typically mixed integer problems (MIP). The computational efforts needed for solving these problems increases drastically with the increase of the network size. One way to overcome this computational difficulty is to develop more efficient and faster algorithms. Another option is to reduce the size of the model by removing parts of the network of terminals and connections. This research is concerned with developing a selection procedure based on parameters of terminals and connections to make a contemplated selection.

The following research question will be answered: how could an intermodal container distribution network be selected in a generic way?

To answer this question, first, intermodal container transportation is investigated in a literature research. This research contains an overview of models and networks used in other researches. Almost all models make use of the same modeling technique, but vary in complexity. Different features are used to more accurately describe the real behavior of a network, for example, capacity constraints on parts of the network and time-dependent parameters of the model.

The important parameters of intermodal container transport are used to come up with an intermodal container distribution network in a generic way. Parameters like, handling and storage capacities of the terminal, transport capacities of the connections and the related cost of performing these actions, are part of the models proposed in literature.

Since multiple aspects in intermodal container transport are important, the following aspects should be considered in the selection procedure:

 The number of modalities served by a container terminal is a logical choice of an aspect to be taken into account. In intermodal container transport the goal is to have several options to transport containers in order to get an optimal transportation solution at a certain time. Having trimodal terminals, serving both rail, barge and road transport, in the network would offer this possibility.

 The second aspect to consider is the capacity of the terminals in terms of handling and storage capacity. In intermodal transport containers are transferred from one mode to another. Terminals offering high handling capacities should therefore receive a higher grade in the selection.

 Third and last aspect in the selection procedure is the capacity of the rail, barge and road connections between the terminals. In the end, intermodal container transport is all about getting a certain amount of containers from one location to another. The connections should allow this amount of containers flowing through the network.

Abovementioned aspects should all be considered in the selection procedure. However, one of the three aspects could be considered more important than the others. Therefore, weight factors can be applied to indicate their relative differences in importance. In this research all terminals are given a grade for each of the three aspects. The total grade, , of each terminal is based on the sum of

the grades for each aspect times their respective weight factors, as illustrated in the equation below:

total modality modality capacity capacity connection connection

S



S



WF



S



WF



S



WF

Where:

- represents the grade for aspect .

However, this equation is quite abstract. Determining the value of the grades for each aspect is an important and difficult task, especially for the capacity and connections of the terminals. Obtaining reliable and a complete range of data would require an extensive research. In this research the capacity of a terminal is graded using the terminal area and equipment installed. The connections of a terminal are graded using data about the infrastructure of different modalities.

The abovementioned selection procedure is evaluated on a test case of intermodal container transport in the Netherlands. In this country a dense infrastructure of terminals, waterways, tracks and roads exist in order to transport a large amount of containers from the ports of Rotterdam and Amsterdam to the hinterland. Scenarios using different weight factors and network sizes are evaluated. The resulting networks all contained a few ‘core terminals’ having high grades on all selection aspects. The remaining part of the network changed with different weight factors.

Further research towards a terminal selection procedure could be in the direction of incorporating distances between terminals selected in the network. In this way a network with a more consistent density will be generated. In the proposed selection procedure there is no constraint on distances, leading to satellite terminals having large distances to the other terminals in the network. However, incorporating this feature would result in an iterative process: selecting terminals, calculating distances and do the selection again. One must be careful not to make the selection procedure too complex, otherwise you could better focus on developing faster solving algorithms. Furthermore, transport demands could be incorporated in the grading of the terminals, because eventually there must be a need for transporting containers to or from a certain region.

Contents

1.4 Structure of the report ... 3

2 Container transport ... 4

2.1 Container movements ... 4

2.2 Players ... 6

2.3 Infrastructure ... 7

2.4 Conclusion ... 9

3 Modeling intermodal container networks... 10

3.1 Reasons for modeling ... 10

3.2 Modeling approaches ... 10

3.3 Networks used in literature ... 11

3.4 Conclusion ... 13

4 Network parameters and selection procedure ... 15

4.1 Parameters of network model ... 15

4.2 Network selection procedure... 17

4.3 Conclusion ... 22

5 Container distribution in the Netherlands ... 23

5.1 Infrastructure in the Netherlands ... 23

5.2 Applying selection procedure ... 26

5.3 Conclusion ... 38

6 Conclusion & Further research ... 40

References ... 41

1 Introduction

Since the introduction of the maritime container as a standardized transport unit in 1955, containerization has grown steadily. Nowadays, the global container fleet counts 34.5 million TEU, according to the World Shipping Council [1]. The largest port of Europe, Rotterdam, handled almost 12 million TEU or 7.1 million containers in 2012 [2]. To expand a port attention should be given to deep-sea transport, but also to developing the so called ‘hinterland’ of a port. A well developed hinterland ensures that a large amount of containers can be supplied and delivered to customers at continental destinations, causing the port to expand. The container distribution network can be seen as the extension of a port deep into the continent. Development of such a network, consisting of terminals and connections, is therefore crucial for the expansion of a port. Eventually, this network will ensure that containers reach their destination, which can either be a shipper or receiver. However, multiple options exist to reach this particular destination, because the network most of the time consists of several terminals and connections. Moreover, one can choose to use various transport modes instead of one. Today, intermodal transport is getting more important for ports in reaching their sustainability goals. Not only to reduce emissions, but also to obtain a more favorable modal split to maintain a good accessibility to the port area. The shift in modal split is towards barge and rail transport. The Port of Rotterdam, for example, is trying to reduce the amount of containers transported by trucks to a maximum of 35% by 2035 [3], [4]. Barge and rail transport should be positively influenced to make them more attractive for transporting containers to and from the hinterland.

1.1 Problem statement

In general transportation of goods should be avoided, because it does not contribute to the value of a product. Therefore, transportation of containers should be done against minimal costs. However, container transport always goes with a time constraint: the containers should be delivered to the receiver in time. This might result in using a more expensive transport modality to ensure timely delivery. Nowadays, one could also consider minimizing emissions which go with transportation of goods. For example, choosing transport modalities consuming less fuel or expelling less carbon or nitrogen dioxide.

This mathematical optimization problem with a certain cost function is the subject of many researches. Different ways to model container distribution networks exist, all with different parameters and features. However, the number of models for intermodal transport networks is still limited. In general these are based on merged unimodal network models and are therefore more extensive. Difficulties arise solving these models, since they are typically mixed integer problems (MIP). A MIP is essentially a NP-hard problem, meaning that computational efforts increase drastically with the increase of the network size. One way to overcome this computational difficulty is to develop more efficient and faster algorithms. Another option is to reduce the size of the model by removing parts of the network of terminals and connections. This research is concerned with the latter case. However, reduction of the network should be done using a certain selection procedure, because one cannot simply remove a terminal from the network without a reason. This procedure is based on the parameters of terminals and connections. The problem of determining the relevant parameters of an intermodal container distribution network and reducing the size of the network is summarized in a research question and related subquestions.

1.2 Research questions

The following research question will be answered in this report:

How could an intermodal container distribution network be selected in a generic way? This research question can be divided in a number of subquestions:

What does a real life intermodal container distribution network look like?

What movements take place in container transport? Which players are involved in the container movements? What does the infrastructure for moving containers look like?

How could an intermodal container distribution network be modeled?

What are the reasons for modeling container transport? Which modeling approaches can be found in literature? What networks are investigated in literature?

How could an intermodal network of terminals and connections be selected, based on their parameters?

How to determine container terminal and connection parameters? How to use these parameters to select a network?

1.3 Approach

This research consists of several parts as indicated by the various subquestions. A literature research is conducted to give answers to most of these questions. The gained knowledge is used to propose a generic selection procedure for an intermodal container distribution network. The working principle of this selection procedure is demonstrated by looking at container transport in the Netherlands. A research towards the parameters of the terminals and connections in the Netherlands is carried out and used as input for the selection procedure. The outcome of the selection is presented and compared to intermodal container transport initiatives and research in the Netherlands.

1.4 Structure of the report

The structure of the report follows the sequence of subquestions. Chapter 2 will deal with describing real container transportation in order to get a general idea about this market and to be able to judge models in literature describing intermodal transportation. The third chapter treats the subject of modeling intermodal transportation. Various modeling approaches and networks can be found in literature having different properties and features. Chapter 4 describes the common network parameters. Furthermore, the selection procedure for terminals and connections in real transport networks will be proposed in this chapter. Eventually, in chapter 5, this selection procedure is demonstrated on the container transportation network in the Netherlands. The report ends with conclusions and recommendations for further research in the sixth chapter.

2 Container transport

To evaluate the modeling of intermodal container distribution networks, first the real life situation should be investigated as indicated by the first subquestion of the research: what does a real life intermodal container distribution network look like? This chapter will look at intermodal container movements and the resources that are necessary to make this possible. These resources can be divided in market players and the infrastructure they make use of.

2.1 Container movements

Demand for freight transportation in general derives from the interplay between producers and consumers of goods (raw materials, intermediate- and finished products) and the significant distance that often separate them. Producers of goods require transportation services to move raw materials and intermediate product to their production plants. Eventually the finished goods need to be distributed in order to meet the customer demands. Shippers, producers of goods, thus generate the demand for transportation.

Carriers fulfill this demand by supplying a transportation service [5]. Since the 1950s standardized containers are used to move almost every piece of break bulk cargo and sometimes dry bulk cargo from shippers to receivers, because containerization has a lot of advantages compared to other methods of transportation. Since containers are standardized, special handling equipment and procedures can be used to load and unload them efficiently. This makes the handling of containers not only faster, but also more reliable. Moreover, containers protect their contents against damage and theft, which makes it a safe way to move goods. All in all, this leads to reduced costs for transporting goods from shipper to receivers. Because of these advantages container transport plays an important role in intermodal transportation and international commerce, nowadays. Container related transportation activities have grown remarkably over the last 10 years and this trend does not show any sign of slowing down [5].

Intermodal transportation is about “The movement of goods in one and the same loading unit or road vehicle, which uses successively two or more modes of transport, without moving the goods themselves in changing modes” [6]. Container transport is one of the best examples of intermodal transportation, since containers can easily be transported using different modalities e.g. vessels, feeders, barges, trains or trucks. This makes it possible to move the containers efficiently between different continents.

The containers which need to be exported are collected at ports and loaded on specially designed container vessels. Arriving at another port the vessels are unloaded and the containers are distributed to the various receivers. Due to efficiency reasons, very large container vessels are constructed for the intercontinental movements regarding ocean navigation. The Triple-E class vessels owned by Maersk Line belong to the largest vessels in the world with a capacity of 18.000 TEU’s [7]. These large vessels can only operate efficiently when not stopping frequently at a number of ports. Moreover, they are too large for the vast majority of ports. This development has a major impact on the inland transportation of containers. A large number of containers is dropped off at a port and must then be distributed to a large number of destinations or other ports at which the large container vessels do not stop. Specially designed transport services are set up to efficiently and economically move containers to continental destinations, such as the European Gateway Services from ECT (Figure 2.1). ECT offers high frequent rail and barge connections between Rotterdam and a rapidly expanding network of inland terminals in the European hinterland. They also apply the concept of ‘extended gates’, which are terminals providing customs services to achieve additional time savings for their customers [8]. All in all, such networks act like an extension of a port deep into the hinterland. A well developed hinterland of a port is crucial for the expansion of the port itself.

Figure 2.2: Inland container movements

The continental or inland movement of containers, in order to collect and distribute goods, is therefore important to look at. Figure 2.2 illustrates possible container movements in the hinterland of a port. As can be seen at the left side of the figure, both full and empty containers arrive and leave a port, because an imbalance exists between the amount of import and export of containers in a country. In China, for example, export is larger than the import of goods. In the Netherlands it is the other way around, more full than empty containers will arrive at the ports and more empty than full containers will leave the port. The ‘reverse logistics’ of empty containers is therefore also important to keep in mind. However, the handling of empty and full containers does not differ a lot and almost the same equipment can be used. Empty containers are lighter and consequently can easily be stacked higher as can be seen in the picture of Figure 2.3. Special ‘empty depots’ are constructed since storage area at deep-sea ports is very expensive. Moreover, maintenance, cleaning and repair can easily be executed at these depots [9].

Figure 2.3: High stacked containers at an ‘empty depot’ [10]

The most basic form of container movement is directly from port to shipper or receiver at which a container is loaded or emptied, as can be seen at the left side of Figure 2.2. In case a receiver is also a shipper of goods, a container can directly be loaded and only full containers will be transported from and to this customer. This so called ‘customized transportation’ does not involve intermediate terminals at which the containers are handled, but uses dedicated services to its customers. Truckload trucking is a typical example of customized transportation. When a customer needs a transportation service a truck driver will travel to the customers designated location, load the container and bring it to the desired destination where it is unloaded [5]. These services are offered both on short and long distances and can also be provided by train or barge companies. ‘Customized transportation’ is not always the appropriate answer for a certain demand.

Parameters like volume, frequency, costs and delivery time can also ask for ‘consolidation transportation’ services in which containers for different customers with possibly different initial origins and final destinations are moved. This ‘consolidation transportation’ involves intermediate terminals and multiple transport modalities forming a certain network of terminals and connections: a hub-and-spoke network as illustrated in Figure 2.4. Containers from shippers and receivers or small regional terminals (nodes 1-9) are first moved to an intermediate point, a consolidation terminal or hub, such as a port terminal or an inland terminal (nodes A, B and C). From this terminal, containers with different origins and destinations are consolidated and moved together using frequent and high capacity ‘shuttle’ or ‘liner’ services to another terminal [11]. These services between the different terminals take advantage of the economies of scale which come with frequently transporting a large amount of containers. Containers arriving at a terminal are eventually transported to their final destination using a ‘customized transportation’ service between nodes A and 1-3, nodes B and 4-7 or nodes C and 8-9. The drawback of this hub-and-spoke network is the increased transportation time due to longer routes and time spent in terminals. Moreover, more chance of damaging the container, or the goods it contains, exists. In some cases it might be more efficient, cheaper or safer to directly transport a container to its destination without using an intermediate terminal. This depends on the performance of the hub-and-spoke network: in a well developed network it will be more interesting to use this transportation service instead of directly moving the container to its destination. Terminals are clearly an important component of consolidation and intermodal transportation systems and their efficiency is vital to the performance of the entire transport chain. A well-known example of consolidation is that of railway services where, first, railcars are grouped together into blocks and moved from their origin to a rail terminal (or shunting yard). After that, blocks are put together to make up a long train and, arriving at a intermediate or final terminal, are decoupled again and brought separately to their final destination [11].

Figure 2.4: Hub-and-spoke network [5]

2.2 Players

The movement of containers in a ‘customized’ or ‘consolidated’ transportation service does involve different players each with their own tasks and objectives. Since container transport is also a market it has a demand and supply side, each with different players needing or offering a certain service [11], [12].

2.2.1 Demand side

The demand side of container transport asks for transportation services. The following players belong to the demand side:

 Shippers (consignors) or receivers (consignees) who actually offer a full or empty container to transport to a specific location.

 Forwarders optimizing logistic for shippers and receivers. They take care of determining the best option for moving the cargo, instruct the logistic service providers and take care of administrative procedures.

 Ocean shipping lines offer a container fleet which can be used to transport goods. They have a demand for a certain number of customers to make optimal use of the containers they use.

 Logistic service providers are companies with logistic assets other than just transport equipment. Think of warehouses, cross-docking platforms, container freight yards and storage areas.

2.2.2 Supply side

The supply side of container transport can be divided into pure commercial players, which need to make money, and public sector players.

Commercial

 Terminal operators offer transfer of containers from one transport mode to another (train, barge or truck) or transshipment from transport equipment to a temporary storage area.

 Rail, barge and shortsea transport operators, who transport the containers between the different terminals.

 Road transport operators performing the local haulage between terminal and customers.

 Intermodal transport operators are trying to sell a full transport service in offering door-to-door or terminal-to-terminal transport. They procure transport and transshipment services from terminal and transport operators and try to optimize the use of the different services.

Public

 Infrastructure managers are concerned with optimizing the use of existing infrastructure and to ensure that it is maintained in good condition. Infrastructure capacity can be assigned to the different users.

 Port authorities run the port area and develop services and facilities for transshipment, transport and logistics services.

 Regional, national and international public authorities are acting in the same way as port authorities and offer certain services at different levels. They also enforce legislation concerning container transport.

2.3 Infrastructure

The physical infrastructure of the container transportation chain exists of two parts: terminals and connections.

2.3.1 Terminals

A terminal can have different tasks in the container transportation chain. In the first place it is a facility at which containers can be transferred between modalities. At a trimodal container terminal, for example, a container can switch between barge, rail or road transport. Furthermore, container terminals offer the possibility to store empty and full containers for their customers. A well equipped terminal can even provide grid connections to store refrigerated containers, called ‘reefers’. The majority of container terminals also offer additional services on top of transferring and storing the containers, like cleaning, repairing and degassing.

Not only can a difference in service level exist between the various terminals, but also in size or capacity. In [13] the following classification of terminals is given:

 Main port terminals: terminals which are located in the port areas of a region. The majority of these terminals have trimodal connections to other terminals in the region and both serve deep-sea and inland traffic. Multiple of these main port terminals are located in a port region. In Figure 2.5 a picture of the enormous ECT Delta Terminal is given, which is a typical example of a main port terminal.

 International operating terminals: terminals not only having connections to the main port terminals, but also with terminals outside the region. These terminals are important for the intercontinental flow of containers. Most of these terminals have trimodal connections with other terminals, like the international operating terminal of Born (Figure 2.6).

 Regional operating terminals: terminals only serving one specific region, like a logistical hotspot or an industrial area. In general these terminals are small and do not serve three modalities.

Figure 2.6: Barge & Rail Terminal Born [15]

Several kinds of equipment are used at a terminal, but only the most common types of handling equipment at inland terminals are presented. The handling equipment can be divided in cranes and mobile equipment.

Cranes

Cranes offer high handling capacities, but are fixed to a rail and are therefore less flexible. They can only stack containers in their own range of operation; hence other equipment will be necessary to move the containers to right locations. Two types of cranes are commonly used at inland container terminals: gantry and rotating cranes, depicted respectively in Figure 2.7 and Figure 2.8.

Figure 2.7: Gantry crane at OCT [16] Figure 2.8: Liebherr rotating crane [17]

Mobile equipment

As mentioned before, mobile equipment will be needed to bring containers to the right location at a terminal, because cranes are fixed to a rail. At inland terminals two types of mobile equipment are commonly used: reachstackers (Figure 2.9) and forklifts (Figure 2.10). Reachstackers can be deployed for every task at a terminal and can even be used to load and unload containers from barges. Small terminals, not having cranes installed, make optimal use of the flexibility of reachstackers.

2.3.2 Connections

In inland container transport three types of connections exist: roads, rail and waterways. Each type has its own characteristics, which are summarized below [11], [20].

 Road container transport is the most flexible type of container transport, but also the most expensive one at longer distances. Normally trucks have a capacity of 2 TEU, but can be bounded to 1 TEU by the maximum axle load allowed at the roads. Road transport is mostly deployed for the local haul between terminal and shipper or receiver (or vice versa).

 Rail transport is bounded by predetermined traffic schedules and therefore less flexible than road transport. However, a lot more containers can be transported in one time. The maximum train length in Europe is 600 meters, which allows for approximately 80 TEU to be transported in one time. In North America double stacked trains are deployed, but in Europe this is not possible due to height restrictions of tunnels and bridges. Another huge restriction in rail transport in Europe is the technical differences in rail networks of the various countries. Differences in rail gauge and type of electrification make it necessary to switch locomotive or even transferring containers from one rail wagon to another. The railway network in Europe exists of a series of connected national railway systems and cannot be seen as one system. As a result, the time and costs of transporting containers can differ a lot. The interoperability and standardization of the European railway network is one of the core activities of the European Railway Agency (ERA) [21].

 Barge transport is heavily influenced by the available infrastructure of rivers and canals. Capacities are restricted by the width and depth of the waterways, but even more by the height of the bridges crossing the rivers and canals. Moreover, the air and water draughts vary due to the fluctuating water level. In Europe the waterways are classified by the Conférence Européenne des Ministres des Transports (CEMT) [22]. An overview of these classes and the corresponding capacities is given Table 2.1.

Table 2.1: Typical container capacity per CEMT class [11]

Class Vessel name Typical TEU capacity Typical TEU configuration

II Kampine barge 24 6x2x2

III Dortmunder 54 9x3x2

IV European class 90 10x3x3

Va Rhine vessel 208 13x4x4

Vb 1x2 push barge 384 13x4x4 + 11x4x4

VIa 2x1 push barge 352 2x 11x4x4

VIb 2x2 push barge 450-500 -

2.4 Conclusion

As stated in the introduction of this chapter an answer is given to the question: what does a real life intermodal container distribution network look like? In general, intermodal container transport is based on a network of terminals and connections, which are used and managed by several players in the container transportation market. Containers will flow through this network from shipper to receiver or vice versa depending on the state of the container: full or empty. If this movement of containers is done using different modalities, we are talking about intermodal container transport. Nowadays, intermodal container transport is getting increasingly important for port areas to reach their sustainability goals and in order to further expand their activities. A shift towards barge and rail transport is needed to reduce emissions and to maintain a good accessibility to the port area. Moreover, a well developed hinterland of a port ensures that a higher flow of containers can be handled in the port areas. This hinterland exists of container terminals which are serving a certain region with economical activities or act like an international gateway to a larger region. These terminals vary in size and services they offer, which is often determined by the capacity and number of connections to other terminals. So called, trimodal terminals serve both rail, barge and road transport and therefore offer a lot of options to move containers. To make optimal use of the options a certain transportation network offers, models are developed. Modeling intermodal container networks and transportation is the subject of the next chapter.

3 Modeling intermodal container networks

This chapter is about modeling intermodal container transport and tries to give an answer to the question: how could an intermodal container distribution network be modeled? First the reasons for modeling intermodal container transport are discussed. After that an overview of modeling approaches which exist in literature is given. Moreover, the networks to which the models are applied are of interest to the research. Are these networks made-up by the authors themselves or are they based on existing transport networks in a certain geographic region? An overview of features, applications and sizes of networks and models will be presented.

3.1 Reasons for modeling

Modeling intermodal container distribution networks is done for various reasons. They are used to analyze and solve various problems at different decision levels for different players in the transport market.

According to [5] intermodal transport issues can be labeled under ‘system design’ or ‘service network design’. With ‘system design’ there is a focus on issues at strategic level concerning the design of the physical infrastructure network: where to locate terminals?, what type and quantity of equipment to install at each facility?, what type of lines or capacity to add?, what lines or facilities to abandon?, and so on. The term ‘service network design’ concerns tactical planning issues i.e. how to use the existing physical infrastructure best? The following questions could be answered with developing a transportation model: on what routes to provide service?, what type of service (mode) to use?, how often to offer service on each route and according to what schedule?, how to route the loads through the physical and service networks?, or how to distribute the work among the terminals of the system? The goal is to satisfy the customers in the most cost-efficient way.

[23] also mentions modeling issues. However, the different problems are categorized in a matrix looking both at the decision level - strategic, tactical or operational – and the key player involved - drayage, terminal, network and intermodal operator. Each player has its own decisions to take. To give an interesting example: an intermodal operator will look at the selection of routing and service at the operational level. This reason for modeling intermodal transport is also given by [24]: determining the optimal routing of container transport over the network to provide cost and energy efficient transport services.

3.2 Modeling approaches

Modeling and controlling container terminals in a more integrated approach has been the subject of researches of the last ten years. These integrated approaches try to catch the behavior of the different transport modes in one model, instead of considering the modes individually [25]. This research area is still in development. Before that, many studies have been performed to realize an improvement of the operation of container terminals by looking at sub problems, but not looking at the transport chain as a whole.

The proposed modeling techniques in the different researches are all based on the same principles, but include different features. In general, an intermodal transport network is modeled as a graph consisting of two interconnected components: links and nodes . The nodes represent the locations of terminals and links are used to model the flow of containers through the physical infrastructure between or at terminals. By giving nodes and links the right properties, the behavior of the transport system can be simulated.

Basically, all researches apply the ‘multiple node method’ to represent an intermodal transport network. It means that every terminal is represented by multiple nodes: one node for each modality served by that terminal. In fact, the graph consists of multiple single-mode graphs , each one forming a transport modality, which are connected to each other at terminals by so called ‘transfer links’. Each single-mode network is represented by a directed graph in which is the set of nodes and the set of links for transport modality (barge, rail, road, etc.). From these single-mode networks a directed ‘super-graph’ is build in which is the set of nodes and is the set of links from the different single-mode networks . Note the set which defines the set of ‘transfer links’ [26] used to transfer containers from one modality to another at a terminal.

The basic structure of the networks in the different researches is broadly the same, but they include different features. The options to define the parameters of nodes and links are numerous. The most basic formulation of these parameters is done in a static way [26], [27], [28]. In those models the

time dependence of the route choice is not taken into account. Beforehand, all parameters of the network are determined and fixed at a certain value. After that, the model is solved and the results are used to make a certain decision.

Some work is done in modeling dynamics in intermodal transport networks. The research in [29] is not specifically about transporting containers, but presents a multimodal network with dynamic link travel times and switching delays (transfer time). Time is accounted for changing from one mode to another and the link travel times are not fixed, but can vary in time. These dynamic travel times result in different routing options for a given origin-destination pair at different times of the day. The same dynamic features are present in [30] where a time-dependent multimodal transport graph is used and costs for crossing a link, both transport and transfer links, are made time-dependent.

Moreover, one can also include constraints to make sure only viable solutions are generated. In [31], a solution is called viable if its sequence of modes is feasible with respect to a set of constraints. This is, in particular, of interest in intermodal transit networks, but can also be applied in intermodal container distribution networks.

The modeling of container distribution networks in [24] is done in more detail and includes more features of real container transport. Furthermore, constraints are added on the capacities of links and nodes and the entering capacity of links. This is done in order to represent the handling capacities of the equipment installed at a terminal to load and unload containers. Moreover, a separate node at each terminal is included to store containers.

3.3 Networks used in literature

Most of the models or algorithms developed to solve a certain problem related to intermodal inland container transport are tested on a network to show their performance and capabilities to solve the problem stated by the authors. According to [30], the used networks can roughly be divided in two kinds of networks: random transport networks and real transport networks. However, the term ‘random transport network’ can better be replaced by ‘self-generated transport network’, because the authors did not randomly construct a network. Most of the time, a well balanced network is given to best illustrate the working principle of a model or to show the performance of a solving algorithm.

3.3.1 Self-generated transport networks

Self-generated intermodal container distribution networks are most of the time used to show the working principle of a certain model or to show the performance of a solving algorithm. The networks used in [24] are clearly an example to show the working principle and features of the model proposed in the paper. As can be seen in Figure 3.1, this network consists of a small number of nodes and links to make this example easy to follow by the reader.

Figure 3.1: Academic example used in [24]

The same holds for [29] in which a four node example is used to show a feature of the algorithm. However, in this paper also more extensive networks can be found to show the performance of the presented algorithm in terms of CPU time with respect to the number of nodes and links. Networks of 50, 100, 500 and 1000 nodes with respectively 168, 276, 1381 and 2747 links are used. In the same way, the capabilities of a hybrid solving approach using the Dijkstra algorithm and Ant Colony Optimization (ACO) are tested on large multimodal transport networks and are

compared with other solving techniques in [32]. The same authors use an identical approach in [30] to illustrate the performance of their PMTDSP algorithm on intermodal transport networks represented by a hyper graph. This hyper graph, shown in Figure 3.2, consists of multiple parallel intermodal transport networks, represented by ‘regional graphs’, connected with each other by ‘bridge edges’. Each ‘regional graph’ is solved individually and used in the global solution via a ‘shared memory model’ making it possible to solve large intermodal transport networks. Networks of 1000, 2000 and 3000 nodes with respectively 3000, 6000 and 15000 links are solved using this algorithm. Furthermore, a real network is used by the authors to test the algorithm: the region of Berlin existing of 3122 nodes and 4306 links. The use of existing intermodal container distribution networks is adopted by more researchers. This type of network will be discussed in the next section.

Figure 3.2: Hyper graph [30]

3.3.2 Real transport networks

Researches in which a real transport network is used for modeling intermodal container transportation most of the time have a different goal compared to researches using self-generated networks. As mentioned before, the latter, are most of the time used to show the working principle of a modeling approach or performance of a solving algorithm. These networks are either small or very extensive. In case of using real transport networks the goal is most of the time improving the container transportation in a specific region. One way to do this is by changing the physical infrastructure: locating new container terminals [26], installing new equipment, adding more or better connections, etc. This so called ‘system design’ is the subject of the study in [26] regarding the Iberian Peninsula, Spain. The research evaluates the effect of adding new terminals at user-defined locations in the region (Figure 3.3).

Another method to improve transport in a region would be changing the control strategy of container transport (‘service network design’) - how to route containers through the network, what schedule to use, etc. In [27], a decision support system is developed to route freight through a certain transport network based on the due date for a specific shipment.

Nowadays, real transport networks can relative easily be extracted from Geographic Information Systems (GIS) [33]. Google Earth is one of the best known examples of GIS technology. Some researchers make use of this powerful tool and develop GIS based transportation networks for a certain region. As part of the 1997 United States Commodity Flow Survey, for example, an intermodal freight transportation network was created based on GIS for use in a freight traffic routing study [34]. In [27], a GIS software package is used to visualize the region being analyzed by the decision support system for routing intermodal freight in a user-defined region.

3.3.3 Network overview

The features, applications, sizes and goals of aforementioned networks and related models are summarized in Table 3.1. The first two columns give the title and author(s) of the specific paper.

The four columns thereafter are used to indicate the nature – self-generated or real network - and size – number of nodes and links - of the network used in the corresponding paper. An ‘illustrative example’ is used to explain or clarify the working principle of a certain model or algorithm. A self-generated network is given the label ‘algorithm test’ if the network is used to show the performance of the model or solving algorithm in that specific study. The differences between those two types of self-generated networks can easily be seen from the number of nodes and links used. In case of an ‘illustrative example’ the number of nodes is around 10 or 20. Contrary, in an ‘algorithm test’ hundreds or thousands of nodes are used. The size of real networks differs a lot. In some papers both self-generated and real networks are presented. In those cases, the size of the respective networks (column 5 and 6) is separated by a forward slash.

Columns 7 to 11 give the features of the used model. In a ‘dynamic’ model some of the parameters are time-dependent resulting in a varying behavior of the model in time. Contrary, ‘static’ models have fixed values for the parameters.

3.4 Conclusion

By studying intermodal transportation networks in literature an answer is given to the question: how could an intermodal container distribution network be modeled? However, the first question to ask is why one would like to model an intermodal transportation network. The reasons for modeling can either be labeled under ‘system design’ or ‘service network design’ indicating respectively the design of the physical infrastructure and planning issues i.e. how to use the existing infrastructure best? The questions arising in system and service network design can best be answered using a mathematical formulation of the problem. In this way an optimal solution to the problem can be given by solving a certain set of equations. The mathematical formulation of the problem is in the shape of a graph consisting of nodes and links representing container terminals and the physical connections between them. The nodes and links have properties which can be adapted to simulate an existing transport network. The models proposed in literature vary in complexity having different features to more accurately describe the real behavior of a network. The total costs and/or time needed for transportation of containers over the network is minimized to give an optimal solution to the problem defined by the user. Using a more complex or representative model will result in a better solution. If a more accurate solution is required one could consider using time-dependent parameters for links and nodes and apply constraints on links and nodes to represent the limitations of the physical infrastructure used: equipment, terminal area, roads, tracks, quay length, etc. The network parameters found in literature will play a role in the network selection procedure proposed in the next chapter.

Table 3.1: Overview of networks in literature Art ic le Au th or(s) Se lf-ge ne ra te d ne two rk Re al n et wo rk N um be r o f no de s N um be r o f lin ks M ul tipl e no de m et ho d Time depe nde nc y Ca pa ci ty co nst ra in ts Co nt ai ne r tra nspo rt M ul tim oda l G oa l Re fe re nc e An economic logistics model for the multimodal inland distribution of maritime containers Fedele Iannone, Sten Thore No Yes, Campania seaport region, Italy 25 182 No Static Yes, on railway links

Yes Yes, road

and rail Highlight and measure the advantages of using 'interports' [28] Modeling a rail/road intermodal transportation system Pierre Arnold, Dominique Peeters, Isabelle Thomas No Yes, Iberian Peninsula, Spain

28 ? Yes Static No No Yes, road

and rail Optimally locating rail/road terminals for freight transport

[26]

A general framework for modeling intermodal transport networks L. Li, R.R. Negenborn, B. De Schutter Yes, illustrative example

No 10 32 Yes Dynamic Yes, on links and nodes

Yes Yes, road, rail and barge Presenting a general framework for modeling intermodal transport networks [24]

Modeling and solution methods for viable routes in multimodal networks Sun Huacan, Li Xuhong, Chen Dawei Yes, illustrative example

No 15 19 Yes Static Yes, maximum number of modal transfers No Yes, road, rail, barge and air Selecting shortest viable route in multimodal freight transportation networks [35] Computer assisted routing of intermodal shipments B.S. Boardman, E.M. Malstrom, D.P. Butler, M.H. Cole No Yes, defined by user of software <

1000 < 10000 Yes Static No No Yes, road, rail, barge and air Determining least cost combination of transportation modes through a network [27]

Best routes selection in international intermodal networks

Tsung-Sheng

Chang Yes, illustrative example

Yes, Taiwan region and Denver (USA)

9 /

112 15 / 407 Yes Static Yes, on links No Yes, road, rail, deep sea and air Selecting best routes for shipments through an intermodal multicommodity network [36] An intermodal optimum path algorithm for multimodal networks with dynamic arc travel times and switching delays Athanasios Ziliaskopoulus, Withney Wardell Yes, algorithm test No 50, 100, 500, 1000 168, 276, 1381, 2747

Yes Dynamic No No Yes, road, rail, barge and air Selecting optimum path in a time-dependent intermodal transportation network [29]

Shortest viable path algorithm in multimodal networks Angelica Lozano, Giovanni Storchi Yes, illustrative example

No 21 51 Yes Static Yes, maximum number of modal transfers No Yes, bus, metro, private Finding shortests viable path in a multimodal transportation network [31]

A parallel algorithm for solving time dependent multimodal transport problem H. Ayed, Z. Habbas, D. Khadraoui, C. Galvez-Fernandez Yes, algorithm test Yes, region of Berlin 1000, 2000, 4000 / 3122 3000, 6000, 15000 / 4306

Yes Dynamic No No Yes, multiple (2,4,8,10) Presenting a parallel algorithm for sloving TDMTP in very large transport networks [30] Intermodal Container flow simulation model and its applications

Qiang Meng,

Shuaian Wang Yes, illustrative example

Yes, east coast

of China 23 / ? ? / ? Yes Static No Yes Yes, road, rail and barge

Developing a container flow simulation model for predicting the effect of new liner services

[37]

A multimode multiproduct network assignment model for strategic planning of freight flows Jacques Guélat, Michael Florian, Theodor Gabriel Crainic No Yes, national freight network of Brazil

1454 10675 Yes Static No, but costs depend on volume on link No Yes, road, rail (electric and diesel) Presenting a normative model for simulating freight flows of multiple products on a multimodal network [38] Solving time-dependent multimodal transport problems using a transfer graph model

H. Ayed, Z. Habbas, D. Khadraoui, C. Galvez-Fernandez Yes, algorithm test No 100, 500, 1000, 2000, 4000 300, 1000, 3000, 6000, 15000

Yes Dynamic No No Yes, multiple (3,4,5) Presenting a hybrid approach for optimizing the time-dependent multimodal transport problems [32]

4 Network parameters and selection procedure

As mentioned in the previous chapter intermodal container transportation can be modeled using a mathematical formulation in the form of a set of equations and a graph . This graph represents a network of terminals and connections. Which terminals and connections to select in a network is the subject of this chapter: how could an intermodal network of terminals and connections be selected, based on their parameters?

In order to answer this question, first, an overview and explanation of some common parameters, which were found in literature, will be given. Secondly, a selection procedure will be proposed based on these parameters or other representative parameters for the terminals and connections.

4.1 Parameters of network model

The models found in literature use the global parameters of container transport. However, determining some of those parameters, without doing an extensive research, is difficult. Furthermore, terminals and especially connections are subjected to change so taking values from different time periods is dangerous. In the sections below an overview and explanation of the common parameters used in literature is given. Only the researches regarding container transport are considered [24], [28], [37].

4.1.1 Nodes (terminals)

Handling capacity, in [TEU/hr] indicates the amount of containers (TEU) that can enter

_{and leave the terminal (node ) through all the connections (links) with other terminals}

at time step . It is determined by the equipment present at the terminal and their individual capacity. A gantry crane, for example, has a higher handling capacity than a reachstacker. The total handling capacity of a terminal can be formulated as given in equation (4.1). As indicated by the equation, the handling capacity for incoming and outgoing containers should be considered as one, because container handling equipment cannot load and unload at the same time. Furthermore, the total handling capacity can vary in time. To give an example: during the night shifts not all the equipment can be operated, because fewer employees are working.

(4.1) _, 1

( )

( )

( )

( )

h k

h

k

h

k

h

k









- is the total handling capacity in [TEU/hr] of node at time step .

- _{and are the handling capacities in [TEU/hr] of respectively the ingoing and}

outgoing flow of containers, together making up the total handling capacity .

- is the individual handling capacity in [TEU/hr] of each piece of equipment at node .

- is the total number of equipment available at node .

Storage capacity, in [TEU] means the number of TEU that can be stored at a terminal (node ).

This parameter can be considered static, because the storage capacity of a terminal will not be different every hour. However, on a longer time base, for example a week or month, this could be another story. Terminal operators can rent some area to temporary store an excess of containers.

Containers are stored in a stack with a certain surface area, height and stack utilization. The space available for stacking is determined by the total area of the terminal minus the maneuvering space needed for stacking equipment. Equation (4.2) can be applied to determine the available storage capacity at a terminal.

(4.2) Ai i i i i

A n

S

a



  





- is the stack area utilization factor, which represents the effective usage of the total stack area available at node . It is determined by the equipment used to stack the containers. Some equipment needs more space for maneuvering than others, which will

result in a lower terminal utilization factor. Reachstackers, for example, use a lot more space than gantry cranes, because they need to turn in order to get a container at the right position. Moreover, gantry cranes can access all container positions from above, but reachstackers need to pick them from the side.

- is the total stack area in [m2_{], which is available at the terminal (node ).}

- gives the height of the stack in [number of containers], which is determined by the equipment used at the terminal (node ). Most reachstackers, for example, can only stack to a maximum height of [containers].

- is the stack utilization factor, which determines the maximum storage density of containers. This parameter depends both on the equipment used at the terminal and the desired transfer time from stack to mode or vice versa. Allowing a higher stack utilization will result in more restacking of the containers to reach a particular container for transporting.

- is the occupied stack area in [m2_{] of a 1 TEU container. With respectively a length and}

width of 20 and 8 [ft] (6,10 and 2,44 [m]) this area is equal to [m2_{] [39].}

Storage cost, in [€/TEU/hr] is calculated for containers staying at a terminal (node ). The height of the storage cost is specified by the terminal operator, who wants a certain payback for its investment in the terminal. The location of the terminal has a lot of influence on the cost of storing a container. Operating a container terminal in a port area requires a higher investment than operating a terminal at an inland location. Consequently, the storage cost will be higher at port terminals. Furthermore, the storage cost for a container is time-dependent. At most terminals one can store containers for free the first few days, after that one must pay for it. This time dependency is depicted in equation (4.3). (4.3)

( )

0

{0,1,..., k

}

k

for k

C k

C

for k







 





- is the storage cost in [€/TEU/hr] at node at time step .

- _{is the last time step in [hr] at which the storage is for free at a terminal (node ).}

Staying longer ( ) one must pay for storing containers. - is the storage cost in [€/TEU/hr] after the free period has expired.

4.1.2 Links (connections)

Transport capacity, in [TEU/hr] indicates the number of TEU that can stay in a link between two terminals, node and , at time step . The capacity of the links between terminals is determined by the number of trucks, trains or barges that can stay in that link at a certain point in time. Each transportation mode has its own characteristics and behavior in time.

Truck container transport is limited by the capacity of the roads, which is strongly influenced by external traffic varying from time to time. For example, during rush hour the capacity of the roads is drastically lower than at midday.

Rail transport is bounded by predetermined slots in the traffic schedule at a certain track, since multiple parties make use of the railway network e.g. public transport, bulk transport or tank transport. Furthermore, the number of tracks available and the maximum allowable speed influences the capacity of the railway connection.

Barge transport is limited by the waterway classification, which indicates the maximum sizes of vessels that can navigate a certain river or canal. This classification depends on the width, depth and curvature of the waterway and the height of bridges crossing the waterway [11]. In Europe, the waterways are classified by the Conférence Européenne des Ministres des Transports (CEMT), which link each waterway to a certain CEMT Class [22].

Transfer capacity, in [TEU/hr] gives the number of TEU that can stay in a link between nodes and . Both nodes are part of one terminal and represent a mode, for example truck and barge. In [24], a separate ‘storage’ node exists to which containers can be transferred. The transfer capacity is limited by the number of cranes, reachstackers or other container handling equipment dedicated to handle containers for a certain mode.

Transport or transfer cost, or in [€/TEU/hr] differ between the various transport modes and terminal equipment.

Using a barge, for example, is a cheap method of transporting containers, because it uses the advantage of ‘economy of scale’. Contrary, using a truck will cost a lot more [11]. Furthermore, transport costs will fluctuate during the day: transporting containers during the night will be more expensive, because the wages of personnel in that shift are higher.

Moving containers across a terminal also involves costs _{, depending on the}

equipment used and the time of the day. A gantry crane will have a higher hourly rate than a reachstacker, but can probably handle more containers in a certain time period. In fact, this is the same as the difference existing between barge and truck transport.

Transport or transfer time, _or

_{in [hr] is the actual time needed to get}

from node to node , which is not static, but time-dependent.

In case of transport, this represents the time to get from terminal to terminal at a certain time step . Each transportation mode has its own characteristics. The speed of trucking will fluctuate a lot during the day and can be very unreliable due to congestions. Contrary, rail transport follows a certain schedule and will therefore be very reliable, almost independent of time. A barge moves very slow and is its speed is influenced by the effects of the tides and the operation of locks and drawbridges.

Transferring containers from one mode to another also involves time, in [hr]. The time needed for transfer and transport differs a lot, both in length and variation. Transfer can be expressed in minutes and, compared to transport, be assumed constant i.e. independent of time . Transport time will have a dimension of hours, or even days, and will fluctuate a lot compared to transfer time.

Entering capacity, in [TEU/hr] is used in [24] to indicate the maximum container flow that can enter a link between node and . This is basically determined by the available equipment to handle containers at node and can never exceed _{. This capacity must be divided over all}

outgoing links of node . Furthermore, one could consider the actual size of the infrastructure available at a terminal in determining the entering capacity, _{. For example, a terminal can}

have a lot of handling capacity, but if it has a short quay or small shunting yard the entering capacity will be limited.

4.2 Network selection procedure

To define an intermodal container distribution network of a certain size a generic selection procedure is developed. This procedure is based on the properties of terminals and connections to make a substantiated selection. Three major steps can be identified in the procedure, which are illustrated in Figure 4.1. The explanation of each step and clarification of the diagram will be done in the following three sections. After, each section the selection step is summarized using Process Description Language (PDL) [40].

4.2.1 Identifying and combining main port terminals (step 1)

Since there is a huge difference between main port terminals and inland container terminals as mentioned in 2.3.1, first, these terminals should be separated from each other. Main port terminals in the same port area should be considered as one big terminal, because otherwise this would have a huge impact on the selection of terminals. Main port terminals have huge handling capacities, good connections and offer all possible transport modalities and are therefore always more preferred than the smaller inland terminals. However, this selection procedure is about generating an inland container distribution network, so main port terminals should not play an important role in this. The following PDL is generated to summarize this part of the selection procedure.

Begin

For number of port areas do For number of terminals do

If terminal belongs to port area then add terminal to set of port terminals of that port area

End End

Combine terminals in sets of port terminals of each port area into one terminal End