Determining the impacts of a human operated Multi Trailer System on Inter Terminal Transport performance; Het bepalen van de impacts van door mensen bestuurde Multi Trailers Systemen op de prestatie van een Inter Terminal Transport systeem

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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 106 pages and 3 appendices. It may only be reproduced literally and as a whole. For

Specialization: Transport Engineering and Logistics

Report number: 2016.TEL.8049

Title:

Determining the impacts of a

human operated Multi Trailer

System on Inter Terminal

Transport performance

Author:

R. A. de Jong

Title (in Dutch) Het bepalen van de impacts van door mensen bestuurde Multi Trailers Systemen op de prestatie van een Inter Terminal Transport systeem

Assignment: Masters thesis

Confidential: no

Professor: prof. dr. ir. G Lodewijks

Supervisor: dr. ir. F. Corman

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FACULTY OF MECHANICAL, MARITIME AND M A T E R I A L S E N G I N E E R I N G

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: R. A. de Jong Assignment type: Master thesis

Supervisor: dr. ir. F. Corman Report number: 2016.TEL.8049

Specialization: TEL Confidential: No

Creditpoints (EC): 35

Subiect: R e v i e w of I n t e r Terminal Transport s y s t e m performance with a human operated Multi Trailer S y s t e m (MTS)

The port of Rotterdam's Maasvlakte I and I I will have eighteen container handling facilities by 2030 with, among others, deep sea and inland terminals, creating a large amount of inter terminal container transport. Previous research has given various demand scenarios and has reviewed several inter terminal transport options. The subject of this thesis is to investigate the effects of human operators, required to operate an Inter Terminal Transport (TFT) system using Multi Trailer Systems (MTS) on transport system performance.

The main research question of this thesis is: What are the additional requirements introduced by the human operated MTS, and what are the effects on the ITT system's performance?

For this the following topics are to be investigated:

e Transport optimization (efficient dispatching, stochastic of transport system operation) • Performance requirements (level of control, control structure)

• Human requirements (Human machine interface design (HMI), deadheading, breaks, reliability)

• Resource requirements (Trailers, trucks, infrastructure) Consequently, the following questions will have to be addressed:

9 Are there additional requirements for an efficient ITT that uses Multi Trailer Systems? » Which additional factors do the human operators add to the system (human in the loop)? • Are the result of the discrete event simulation and integer-programming models still accurate,

or do they need revising/updating to account for additional uncertainties and input from the human operators?

® Are there ways to validate the discrete event simulation and integer-programming models when a human operated MTS is chosen as the means of ITT?

The report of this master thesis will be arranged in such a way that all data is structurally presented in graphs, tables, and lists with belonging descriptions and explanations in text.

TUDeift

Delft University ofTechnoIog y

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Summary

This MSc thesis is part of the project: “Innovative Concepts for Inter Terminal Transport on

Maasvlakte 1 and 2 at the Port of Rotterdam” which is a collaboration between the Port of Rotterdam Authorities, Erasmus University Rotterdam and Delft University of Technology [1].

Container transport through the port of Rotterdam is still increasing and will create an amount of inter terminal transport by 2020 that can not be transported with today’s transport means. Therefore, the port of Rotterdam’s goal is to create an Inter Terminal Transport (ITT) system that utilizes the ‘interne baan’ road network to transport the containers between terminals. The TUDelft’s research project “Innovative Concepts for Inter Terminal Transport on Maasvlakte 1 and 2 at the Port of Rotterdam” has so far determined a number of ITT configurations, which have been implemented in a simulation model.

Current developments have resulted in a preference for a human operated ITT configuration that uses Multi Trailer Systems to transport containers. The current simulation does not consider in detail the effects of human operators and the additional complexity of the MTS configuration. The objective of this research is to obtain a more detailed and accurate representation of the human operated MTS ITT configuration, and to re-evaluate the system’s performance. The adaption of the simulation model by Schroër [2] will involve the introduction of additional variables as Schroër’s simulation [2] model has been designed to compare different ITT configurations and therefore does not take into account some variations in MTS configuration, nor the human operator that is required to operate the MTS.

Several additional variables have been identified and implemented into the simulation model. To represent the requirement of the human operators, shift changes, breaks, and a method to reduce overdue shift change have been implemented. To better represent the MTS a limited number of trailers together with processes to regulate secondary logistics have been implemented into the simulation model. The loading process is now controlled by a threshold determining what a full trailer set should be, in terms of the minimally loaded number of TEU and a threshold that allows containers to be loaded some time before their final start time. These thresholds are further referred to as the full trailer threshold and the MTS load time threshold. For the secondary logistics a threshold value is determined to control when a terminal starts requests for the transport of empty trailers or when it combines requests for empty rides of MTS trucks with that of empty trailers. The main reason for having a MTS load time threshold is to compensate for unexpected delays, delays not included in the calculated expected handling time. These delays can be waiting for terminal equipment, longer load and unload times, waiting for MTS trucks, and waiting for the availability of empty trailers.

The review of results from preliminary simulation runs identified that the input demand consisted of a percentage of transport tasks that the system would not be able to fulfil without resulting in non-performance. This unavoidable non-performance is determined by comparing the time available with

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unavoidable overdue, can still arrive on time as some parts of the transport, loading, unloading or waiting can be less that the expected time. However, this is something that a real life ITT system will encounter and here the system should not be held accountable for the non-performance that resulted from transport tasks that do not allow enough time for the ITT system to completed the task in a predetermined expected handling time. This also points out the importance of an accurate, realistic and representable calculated expected handling time.

In its original state the simulation model of Schroër [2] allows for a second filtering in the process where the trailer sets are coupled to MTS trucks as if the shunting of trailers is possible. However, the shunting and consequent coupling and decoupling of trailers to increase the loading rate in this way was determined to be unfeasible in Chapter 4 as this would require reversing with more than two trailers, which is not done in practice as it requires technologically advanced control to keep all the trailers tracking in the same direction. This part of the original model can thus be seen as too optimistic and as a result the modified model with the implementation to limit the number of trailers switched on, returns lower loading rates as containers loaded together onto the same trailer set stay together.

Several values for the empty trailer request threshold and the full trailer threshold have also been tested. The results show that the avoidable non-performance can be lowered by choosing optimum values for the full trailer threshold and for the request empty trailer threshold. However, a pitfall has been discovered in the current method to request an empty ride and the way an empty ride is combined with the transport of empty trailers. If the terminal control decides to request an empty ride, as it needs a MTS truck to transport a trailer set, it also checks if it needs empty trailers. If the terminal is in need of empty trailers, the empty ride is converted in an empty trailer request, as this will also bring a MTS truck to fulfil the empty ride request. The problem is, if the request for empty trailers fails, because there are not enough trailers available at other terminals, or the terminal with empty trailers available does not have a MTS truck to transport them, the requesting terminal does not receive a MTS truck and the transport task is delayed. This part of the simulation model will require updating to solve this problem. If the main request of a terminal is to request an empty ride of a MTS truck, and it is also in need of empty trailers, it will request an empty ride with empty trailers. If this request for empty trailers fails, it should return to the request for an empty ride in order not to delay the transport of containers that are already loaded onto trailer sets and are ready to be

transported.

The results also show that, with the input demand used, the lowest avoidable non-performance is achieved with a lower full trailer threshold of 5 and 7 TEU. This is in line with the reasoning that the capacity of the MTS with 10 TEU is high and will in most circumstances not be fully utilized. The recommendation for future research is to investigate if this maximum capacity can be lowered without affecting the performance. This research shows that, with the average loading rate, which was in most experiments between 30% and 50%, it is possible to lower the maximum loading capacity.

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Finally, the additional requirements identified for the drivers of MTS trucks, the breaks and shift changes are tested to review what the impact of introducing human operator requirement into the model are. Results in Chapter 9.5 show that driver breaks and shift changes increase the avoidable performance and too late times. However, the overdue reduction procedures of shift changes, prioritizing transport tasks and stopping tasks that will cause overdue shift changes unless they are urgent, has a more profound effect on the average too late than expected. This shows that future research into the prioritization in order to more effectively utilize the recourses of MTS trucks and trailers is necessary and that it is possible to improve the performance of the system. The

prioritization can be part of a more advanced means of controlling transport with collective decision making to overcome some of the problems identified. The control used here is on a first come first served basis when requesting MTS trucks and trailers.

Further consideration should be made to reduce waiting time for terminal equipment. A solution can be to adapt the loading controls, the full trailer threshold and the MTS load time threshold, to the demand and utilization of the MTS trucks. In periods with low demand and utilization of MTS trucks the loading controls can be set in such a way that more containers are loaded. Increasing the MTS load time threshold and lowering the full trailer threshold will result in lower loading rates; however, this will increase the avoidable non-performance as the demand is low, reducing the number of transport tasks. In addition to this method to spread the demand as much as possible, a

recommendation is to investigate the loading and unload rates, to review if these can be described as exponentially distributed in a real world ITT system, and if terminals can take precautions to lower loading and unloading times by reducing transport times from the stack to the MTS trailers.

With these results and conclusions the main research question that states: What are the additional requirements introduced by the human operated MTS, and what are the effects on the ITT system’s performance? is answered, as the additional variables and requirements for both the human operator and the MTS have been identified, and the effects on system performance have been investigated, established and described.

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Samenvatting

Deze master thesis is een onderdeel van het project “Innovative Concepts for Inter Terminal Transport on Maasvlakte 1 and 2 at the Port of Rotterdam”, een samenwerkingsverband van het Havenbedrijf Roterdam, de Erasmus Universiteit Rotterdam en de Technische Universiteit Delft [1].

De doorvoer van containers door the haven van Rotterdam groeit en zal in 2020 een dusdanig hoog niveau hebben bereikt dat het transport van containers tussen de verschillende terminals, het Inter Terminal Transport (ITT), niet meer gedaan kan worden met huidige methode. Hiervoor heeft het Havenbedrijf Rotterdam het plan om het interne baan wegen netwerk te gebruiken om containers tussen terminals the transporteren. Het research project “Innovative Concepts for Inter Terminal Transport on Maasvlakte 1 and 2 at the Port of Rotterdam” van de TUDelft heeft tot dusver een aantal mogelijke ITT configuraties voor dit transportsysteem bepaald en geïmplementeerd in een

simulatiemodel.

Huidige ontwikkelingen in de haven van Rotterdam resulteren in een voorkeur voor een ITT configuratie welke gebruikt maakt van door mensen bestuurde voertuigen om hiermee

werkgelegenheid te creëren. Het huidige simulatiemodel houd geen rekening met de details welke werknemers in de vorm van chauffeurs en de extra complexiteit die een MTS ITT systeem

introduceert. Het doel van dit onderzoek is om een meer gedetailleerde en werkelijkheidsgetrouwe representatie van het MTS systeem te definiëren en te implementeren in het huidige simulatiemodel om de werking van het systeem te kunnen evalueren. De aanpassingen aan het simulatiemodel dat door Schroër [2] is ontworpen en geprogrammeerd, zijn onder andere de introductie van bijkomende variabelen omdat het simulatie model van Schroër [2] is ontworpen is om verschillende ITT

configuraties te vergelijken en daarom geen rekening houdt met variaties binnen de MTS configuratie en ook niet met de chauffeurs die noodzakelijk zijn om de voertuigen te besturen.

Dit onderzoek heeft meerdere bijkomende variabelen geïdentificeerd en geïmplementeerd in het simulatiemodel. Ploegendienstwisselingen en pauzes zijn als noodzaken voor chauffeurs

geïmplementeerd in het simulatiemodel, samen met een methode om overtijd, door verlate

ploegendienstwisselingen te reduceren. Het laadproces in het simulatiemodel wordt nu gestuurd met behulp van een drempelwaarde, welke bepaalt hoeveel TEU aan containers met dezelfde bestemming beschikbaar moeten zijn om een ‘volle’ MTS te laden, en met een tijdsdrempelwaarde die toelaat om containers te laden voor de bepaalde uiterste starttijd van de container. Deze drempelwaardes worden verder de laaddrempel en de laadtijdsdrempel genoemd.

Voor de secundaire logistiek van MTS trailer sets is een extra drempelwaarde geïntroduceerd die bepaalt wanneer een terminal lege ritten met trailers gaat initiëren en waar mogelijk gaat combineren met lege ritten van MTS trucks. De reden om een tijdsdrempelwaarde te gebruiken is om waar mogelijk transport taken eerder te laten starten om zodoende speling te creëren om onverwachte vertragingen te kunnen opvangen.

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De pre-evaluatie van de eerste testen met het simulatiemodel hebben geïdentificeerd dat een deel van de transportvraag, welke in de form van een inputfile in het simulatiemodel wordt ingevoerd, bestaat uit taken welke niet binnen de beschikbare tijd van de transporttaak kunnen worden voldaan en zo er voor zorgen dat containers te laat komen. Het percentage van vervoerde containers die te laat komen wordt non-performance genoemd. Het deel wat in eerste instantie al niet op tijd had kunnen komen is de onoverkoombare non-performance of unavoidable non-performance. In sommige gevallen kunnen transporttaken, die voortijdig geïdentificeerd worden als onoverkoombaar te laat, alsnog op tijd arriveren doordat alles in het transport meezit en de tijd korter uitvalt dan de berekende verwachte verwerkingstijd. Deze kenmerken van dit transport zijn realistisch en zijn kenmerken die in

werkelijkheid ook voorkomen. Het systeem mag echter niet afgerekend worden op non-performance welke resulteert uit deze vorm van overmacht. Tevens benadrukt dit hoe belangrijk een nauwkeurige en realistische bepaling van de te verwachten verwerkingstijd van transportopdrachten is.

In zijn originele staat laat het simulatiemodel van Schroër [2] toe om containers, welke al op trailers geladen zijn, wederom te filteren en zo het aantal containers per rit the verhogen in het proces waar de MTS truck aan de trailer-set gekoppeld wordt. Het simulatiemodel werkt dan alsof het mogelijk is om individuele trailers te rangeren. Dit is in Hoofdstuk 4 geëvalueerd is en onpraktisch bevonden omdat het zou beteken dat MTS trucks met meer dan één trailer tegelijk achteruit moeten rijden wat in de praktijk zonder zeer geavanceerde technische hulpmiddelen niet mogelijk is. Vastgesteld kan worden dat dit deel van het originele simulatiemodel te optimistisch is want wanneer de

implementaties aangezet worden, zodat het aantal trailers beperkt wordt en het laadproces aangepast is, valt de gemiddelde laadratio lager uit. Dit komt omdat containers die nu geladen worden op een trailer-set bij elkaar blijven als de trailer-set gekoppeld wordt aan de MTS truck.

Meerdere verschillende waarden voor de drempelwaarde van terminals om lege ritten met lege trailers te initiëren en voor de laaddrempel, die het aantal TEU voor een volle trailer set bepaalt, zijn getest. De resultaten laten zien dat de voorkombare non-performance verlaagd kan worden door de juiste waarden te kiezen. Bijkomend is geconstateerd dat in de huidige aanpassing van het simulatie model een probleem kan optreden wanneer terminals een lege rit van een MTS truck combineren met een lege rit van trailers. Als in deze situatie het aantal trailers bij andere terminals dusdanig laag is of er zijn geen MTS trucks beschikbaar bij de terminals met wel genoeg lege trailers, dan lukt het de terminal niet om een lege rit te krijgen en op die manier kunnen containers excessief verlaat worden. Dit deel van het simulatie model vraagt om een aanpassing zodat terminals wel een MTS truck kunnen krijgen als de vraag om lege trailers te krijgen faalt.

Verdere resultaten laten zien dat, met de huidige input van de transport vraag, de laagste

voorkombare non-performance met een laaddrempel van 5 en 7 TEU wordt gehaald. Dit klopt met de redenering dat de capaciteit van de MTS met 10 TEU aan de hoge kant is en dat in de meeste gevallen de capaciteit niet volledig wordt benut. De aanbeveling is om in toekomstige onderzoeken te

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experimenten tussen de 30% en 50% ligt en dat het dus mogelijk moet zijn om de maximale laadcapaciteit van de MTS te verlagen.

Tot slot, de bijkomende variabelen die betrekking hebben op het personeel, de chauffeurs.

Ploegendienstwisselingen en pauzes zijn geïdentificeerd en getest om de impact te bepalen op het ITT MTS systeem. De resultaten in Hoofdstuk 9.5 tonen aan dat de ploegendienstwisselingen en pauzes resulteren in een hogere voorkombare non-performance en gemiddelde te laat tijden. Geconstateerd is dat de methode om de te late ploegendienstwisselingen te reduceren meer effect heeft op het systeem dan verwacht. Het filteren van transport taken op urgentie en de kans dat een MTS te laat op zijn bestemming is om de ploegendienstwisseling tijdig af te ronden resulteert in een lagere

gemiddelde te laat tijd. Dit toont aan dat een prioritering van transporttaken en het gebruik van de resources, de MTS trucks en trailers, de werking van het transport systeem kan verbeteren en het is van belang voor toekomstig onderzoek om naar deze mogelijkheden te kijken. Het prioriteren van de transporttaken kan mogelijk een deel vormen van een meer geavanceerd besturingssysteem waarin de terminals collectief een beslissingen nemen om de beschreven problemen te voorkomen.

Verdere aanpassingen kunnen gedaan worden om de wachttijden voor terminal equipment te reduceren. Een oplossing zou zijn om de drempels welke gebruikt worden om het laadproces te reguleren variabel en afhankelijk van de transportvraag en beschikbaarheid van MTS trucks en trailers te maken. In perioden met weinig transportvraag en hoge beschikbaarheid kunnen de drempels zodanig zijn dat containers eerder worden geladen. De transportvraag kan zo verdeeld worden om te voorkomen dat pieken hoger worden door containers welke lage prioriteit hadden voor de piek maar in een periode met een hoge vraag van prioriteit veranderen. Verder wordt aanbevolen om in

toekomstig onderzoek dieper te kijken naar de laad- en lostijden welke nu exponentieel verdeeld zijn. Klopt deze exponentiele verdeling van laad- en lostijden en kunnen ze worden beperkt door transport tijden van de stack van de terminal naar de gereedstaande MTS trailer-set te reduceren?

Met deze resultaten en conclusies is de hoofdonderzoeksvraag: Wat zijn de bijkomende

Variabelen die worden geïntroduceerd door de keuze voor een door mensen bestuurde MTS ITT systeem en wat zijn de effecten op de performance? beantwoord. De bijkomende variabelen zijn geïdentificeerd en de effecten op het ITT systeem zijn onderzocht, gevonden en beschreven.

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List of abbreviations

AGV = Automated Guided Vehicle ALV = Automated Lifting Vehicle DES = Discrete Event Simulation FEU = Forty-foot Equivalent Unit HF = Human Factors

ITT = Inter Terminal Transport kmh = kilometres per hour MTS = Multi Trailer System

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1 Introduction

This MSc thesis is part of the project: “Innovative Concepts for Inter Terminal Transport on

Maasvlakte 1 and 2 at the Port of Rotterdam” which is a collaboration between the Port of Rotterdam Authorities, Erasmus University Rotterdam and Delft University of Technology [1].

1.1 Inter Terminal Transport developments

Container transport through the port of Rotterdam is still increasing and will create an amount of inter terminal transport by 2020 that can not be transported with todays transport means. It is therefore a vision and an objective of the port of Rotterdam to create an Inter Terminal Transport (ITT) system that utilizes the ‘interne baan’ road network of the Maasvlakte 1 and 2, shown in Figure 1.1, to transport the containers between terminals. The TuDelft’s research project “Innovative Concepts for Inter Terminal Transport on Maasvlakte 1 and 2 at the Port of Rotterdam” has so far determined a number of ITT configurations, which have been implemented in a simulation model to evaluate each ITT configuration’s performance. In this research a performance advantage of an ITT configuration using AGV’s/ALV’s has been revealed.

Figure 1.1. Maasvlakte 2, [3]

However, current developments have resulted in a preference for a human operated ITT configuration that uses Multi Trailer Systems to transport containers. The current optimization and simulation does not consider in detail the effects of human operators and the additional complexity of the MTS configuration. Without further research it is possible that the more detailed representation of the MTS configuration will introduce additional constraints as well as opportunities as a result of its loading

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capacity of more than one container. Additional research into the effects of human operators, the constraints and possibilities of a MTS ITT configuration are therefore needed.

1.2 Research objectives

The objective of this research is to obtain a more detailed and accurate representation of the MTS ITT configuration, and to re-evaluate the system’s performance by comparing the adapted simulation model with the non adapted. The adaption of the simulation model by Schroër [2] will involve the introduction of additional variables as Schroër’s simulation [2] model has been designed to compare different ITT configurations and therefore does not take into account some variations in MTS configuration, nor the human operator that is required to operate the MTS.

The more detailed representation of the MTS ITT configuration is achieved by adding elements and attributes, and by managing some of them as resources of the ITT transport process. Additional elements and attributes can be identified in the MTS as well as the human operators. Some of these will affect the systems performance in a constraining manner, and others could introduce

opportunities, giving, for example, more flexibility.

This MSc project’s objective is to investigate, and ultimately list the additional elements and attributes the MTS ITT configuration introduces, and to evaluate their effect on the systems performance. Furthermore, when additional elements introduce additional opportunities, for example, different dispatch and delivery strategies, the goal of this project is to evaluate and verify if and how they can contribute to improving the system’s performance.

Schroër’s simulation [2] model defines the key performance indicator of system performance as the “non-performance” of container or the tardiness of containers. Schroër’s other performance indicators are vehicle loading rates, vehicle waiting and idle times, the number of idle vehicles and the distances travelled. However, the importance of human operators is overlooked. With the introduction of additional elements and attributes to represent the human operator and the more detailed

characteristics of the MTS configuration, comes the need to introduce further performance indicators which give an insight into the effects of the modelling of human operators on the systems

performance.

It is a goal of this thesis to investigate the effect of the introduction of the human operators into the simulation model on performance, and to review the significance of this introduction. Furthermore, this research will resolve the question whether the hypothesis, that the human operator should not be disregarded from the ITT simulation model, or even any transport simulation model where systems that rely on human operators are modelled and compared, is valid.

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1.3 Approach

By introducing human factors with the required resource management into Schroër’s simulation model, the simulation model can be adapted to accommodate MTS operational decisions and improved resource management. The operational decisions to be introduced are to determine which dispatch and delivery strategies and human resource management strategies are suited to the ITT demand. To accomplish this, the effect that the spread of the demand over time as well as the variety of the origin to destination combinations that containers have on the performance of the ITT will need to be reviewed. Furthermore, the demand and variety over time, split into working days and shifts can be investigated to review if it can be described as a repeating cycle that could be used to spread the deployment of personnel over the shifts.

Different spreads and varieties can also be used to define effective dispatch strategies by again varying the number of MTS, the configurations of up to 5 trailers and the decision to decouple sets of trailers or individual trailers. In addition to choosing an effective dispatch and delivery strategy the insight into the effect of different demand scenarios on ITT will aid in introduction of correct and efficient operator planning with breaks and shift changes.

If the results of the simulation runs indicate that there are significant time windows, of personnel shifts or full working days, where demand is low but the variety of transport tasks is high or vice versa, different strategic decisions can be applied depending on the time window to cater for each different situation. For example, the decision to perform a continues collect and deliver strategy can be made when demand is low but the variety of transport tasks is high. This strategy, in which a MTS travels around on a planned route and visits terminals that have indicated that they need the ITT system or are a destination of one or more containers on board, is ideal for situation with load demand and a high variety. In addition to the different transport strategies that can be chosen the human resources, as well as the number of MTS trucks as they are directly related to each other, can be managed differently according to the transport demand of each shift or working day.

The main goal of this research is to adapt Schroër’s simulation model by enabling it to be used to analyse the more complex and detailed properties of the human operated MTS ITT configuration and their effects on system performance. The overall goal of this type of research is to find and test methods to minimalize transport costs whilst preserving a high level of performance.

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1.4 Contents of this report

In Chapter 2 the details of the ITT MTS configuration and the conception of the modifications to be made to the simulation model are explained by first reviewing the previous research and the research that has been done after the finalization of the simulation model by Schroër. Chapter 3 investigates and identifies the variables that can be implemented to more accurately represent the MTS ITT system and concludes by discussing the chosen variables that will be implemented into the simulation model. Chapter 4 then further investigates and formulates the different operational and decision making strategies that are applicable with the different variable of Chapter 3.

The methods to implement the strategies and variables form chapter 3 and 4 are described in Chapters 5 and 6, after which the process to verify the implementation and other modifications that have been done to the simulation are discussed in Chapter 7. Chapter 7 also reviews the problem concerning the validation.

Chapter 8 describes the analysis methods, the required in and outputs of the simulation model and the methods to determine the avoidable and unavoidable non-performance.

Chapter 9 consists out of the experiments, result and conclusions. The experiments are elaborated and the setup of the required simulation runs is discussed.

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2 The MTS ITT configuration

2.1 Summary of previous research

Part of the founding research by the TUDelft was done by Duinkerken et al. [4], in which the MTS ITT system is described as a separate manned traction unit (FTF, Floor Truck Fabriek) and a set of trailers, the MTS, that is capable of transporting a maximum of 10 TEU.

As part of the project: “Innovative Concepts for Inter Terminal Transport on Maasvlakte 1 and 2 at the Port of Rotterdam” [1], Frans Nieuwkoop [5], has created an IP-model to optimise each individual ITT configuration, and the results for the MTS are, according to Nieuwkoop, reliable, assuming that there is a sufficient transport demand at each terminal to load an MTS up to its capacity of max 10 TEU without delaying the containers. Furthermore, the model clustered terminals to simplify and speed up the calculations. However, Nieuwkoop [5], does mention on page 60 of his thesis report, that this might give unreliable results in cases were transports vehicles with a capacity of more than two TEU, like the MTS are used.

The simulation model that this research uses to further investigate the MTS ITT configuration has been created by Herbert Schroër [2]. His research and simulation model describes a MTS ITT system similarly to Duinkerken et al. [4], but does not mention if the MTS truck-trailer combinations drive with a fixed number of 5 trailers or just the number needed to transport the container allocated to it. Furthermore, the simulation model assumes that an unlimited number of trailers is available at each terminal.

To investigate if this assumption is reasonable, the number of trailers that is needed and their location will need to be checked. If either an excessive number of trailers, or an imbalance of trailers divided over the terminals is found, the simulation model will need to be reconfigured. An excessive number of trailers might require smarter planning, which can be achieved by predicting future transport demand using the simulation model’s ITT demand input. The imbalance of trailers divided over the different terminals can be addressed by introducing trailer ‘empty moves’. This will, consequently introduce a secondary logistic problem, namely the integrating of additional ‘empty moves’ into the current transport demand.

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2.2 Updated demand scenarios

Since the design of the simulation model an updated version of the demand scenarios has been made by de Lange in his research assignment: “Generator for future inter-terminal container transport demand scenarios on the Maasvlakte 1 and 2” [6]. The basis for de Lange’s research and the

development of his demand generator is the research of Gerritse’s [7]. Gerritse used the “Port Vision 2030” from the Port of Rotterdam [8] to create scenarios of container flows between terminals, service centres and empty container depots. With these flows he devised a way to determine a basis for the demand scenarios for the ITT of containers. The generator made by de Lange has generated the ITT demand scenarios for the three different growth scenarios namely, Low Growth, High Oil Prices, European Trend and Global Economy. Unfortunately, only three demand scenarios where available at the time of this research and they where indicated as 72pc, 83pc and 100pc. The

corresponding database files attached to these output data sets of the runs of the demand generator indicated that the demand scenario 100pc was run with a yearly total throughput of container in the Port of Rotterdam of 27.22 million TEU. The output data sets of respectively 83pc and 72pc, were run with 22.06 million TEU and 18.91 million TEU. It was unfortunate that the report by de Lange was not clearer on the three demand scenarios that were produced with his generator, and also that the demand generator was not available to perform a re-run in order to review and possibly to update the demand scenarios.

The number of containers that are generated per hour are plotted in Figures 2.1, 2.2 and 2.3, for demand scenario 1, 2 and 3 respectively. Each spike in these graphs occurs during one week, thus the demand is less in weekends. Furthermore, a month is set a 4 weeks and the total length is three months, the demand varies per month, which can be seen in the graphs. The demands in the months in all three scenarios increase per month with the last month having the highest demand.

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Figure 2.2: Containers generated per hour in demand scenario 2.

Figure 2.3: Containers generated per hour in demand scenario 3.

The variations in demand over each week and that the demand rises each month will result in the simulation having to stabilize again and again. Especially the increases each month are a down side and can affect the accuracy of the results. Therefore, the author recommends that the demand scenarios are reviewed for future research. Starting with a month with high or medium high demand and finishing with a month with medium or low demand would allow the simulation model to stabilize, and more representable and accurate results can be extracted. The author questions if the variation of the demand over each week is realistic, especially the maximum between the midweek and weekend of, for example in demand scenario 3 the first week, about 100 containers per hour. Would the demand show less variation as the ITT has so many sources that produce transport requests?

To conclude, this present research has focussed on the adaptation of the simulation model to

investigate the effects of the human operator and other additional variables that can be introduced to represent an ITT configuration using MTSs in more detail, and has, therefore, not performed an in-depth research into the demand scenarios and their calculation and generation. The monthly

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20 variations and starting with a month with lower demand results in the simulation model to requiring to adapt to the higher demand each consecutive month. To achieve a stable result a simulation time of at least the total time of the demand scenario and possible even looping to finish in the starting month with the lowest demand is required. Therefor to achieve stable results the choice has been made to modify the length of the input demand file to only include the highest month. This will allow for shorter simulation times and will test the system to the highest demand. Shorter simulation times are welcome as the time for one simulation of about 1000 hours can exceed 2 to 3 hours.

2.3 The MTS configuration

The MTS configuration is a container transport system that is comprised of multiple Multi Trailer System (MTS) units consisting of a truck or manned traction unit and up to 5 trailers, as depicted in Figure 2.4, each capable of carrying 2 TEU from either one FEU or two TEU containers. Fully loaded the MTS can carry 10 TEU at a speed of 30 kmh.

Figure 2.4: an MTS being loaded, [9].

2.4 The simulation model

The simulation model by Herbert Schroër’s [2] is a discrete event simulation model that has been made using Delphi [10], an integrated driver electronics programming tool using Object Pascal with the addition of TOMAS [11], a Tool for Object-orientated Modelling And Simulation. The simulation model is dedicated to finding the best ITT configuration and therefore compares different

configurations utilizing different types of vehicles, namely the AGV, ALV, MTS, truck and barge. To achieve this the model has made some assumptions, specifically, concerning the MTS. Schroër’s simulation model [2] assumes that an unlimited number of trailers is available. The reasoning behind this assumption is that the performance of the MTS system will be slightly better than with a limited

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number of trailers, however, with proper scheduling, Schroër states that the performance “should be roughly the same”.

The author of this report’s comments on this statement are, that this assumption relies heavily on the implementation of proper scheduling algorithms for the MTS system, and as these algorithms

introduce a level of complexity and control, it is difficult to oversee the consequences on total system performance. The scheduling of an MTS system, with dispatch and delivery strategies as well as several primary decisions, for example, to couple or decouple trailers can quickly introduce a considerable number of additional variables, whose impact on performance is not clear and thus should not to be underestimated.

Main elements and attributes

2.4.1

The main elements and attributes of Schroër’s simulation model are presented in Table 2.1 which is a replica from the original in Schroër’s report [2], however categorized on a subsystem basis with the terminal, the transport system and the container generation as subsystems and with some different remarks.

Subsystem: Elements: Remarks:

Terminal Terminal Location as destination and origin, queues containers at arrival for further handling by the Terminal Equipment.

Terminal Control Interacts with the ITT system to request empty rides and initiates transports.

Terminal Equipment Load and Unloads containers at the Terminal. Quay Crane Not used in this research as it is only used when

barges are selected as a means of transport.

Transport system Road Part of the ITT network to determine the distance and routes between origins and destinations. Intersection A crossing of roads which introduce delays due to

waiting to ITT transport tasks

Node Part of the route-planning algorithm where all location are represented as a node.

Barge For transport over water, not used in this research.

Vehicle In this research the MTS is chosen as the transport vehicle.

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22 Container

generation

Container The entity that is transported, either a TEU or a FEU container.

Generator Generates containers according to the demand scenario that is used as input.

Urgency Check Checks the Final Start Time of containers and compares that to the current time to determine if a container is categorized as Urgent.

Table 2.1: Main elements and their attributes

Container flows

2.4.2

The general flow of containers, in Schroër’s simulation model’s MTS configuration, from origin to destination, follows a path that consists of several consecutive queues. After a demand to transport a container is generated, the container is then placed in a queue at the origin terminal and queues there waiting to be transferred by terminal equipment to a trailer or trailer set. The trailer or trailer set is modelled as two second queues called the MyMTSSelectContainer, for the first container of a set of containers to the same destination and the MyMTSLoadContainerQ for the rest in order that

containers that have been selected and collected with the same destination or as part as a set of containers with an urgent container are known. The MyMTSSelectContainer now functions as the trigger for the terminal control as the containers in this queue represent either a full set of containers to one destination or an urgent container with other containers that where available with the same destination. The terminal control now orders a truck to transport the containers to their destination. The terminal control further monitors the MyMTSLoadContainerQ for urgent containers that are required to leave to be within the predetermined time frame to arrive at its destination terminal. Any container found to be urgent is also put into the MyMTSSelectContainer.

When a MTS arrives at its destination the manned traction unit or truck is uncoupled from the set of trailers, which enter a queue called the MyMTSUnloadQ, where they wait to be unloaded by terminal equipment. The manned traction unit enters a queue called the MyIdleVehicleQ, where it waits for its next transport task, which can be either an empty ride to another terminal or a transport request from the terminal where it is waiting and idle to transport the containers to another destination.

The unloading of the trailers is done by terminal equipment and is similar to the ALV’s unloading process where terminal equipment needs to unload the containers from a container platform. The container platforms can contain up to two TEU containers or one FEU container that have been placed onto it by the ALV, which is comparable to one MTS trailer. However, the number of platforms for the loading and unloading of ALVs is limited to 2 of each, as specified on pages 52 and 54 in Schroër’s report [2].

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The selection procedure of selecting containers with the same destination whilst checking if they are not overdue to leave is unique to the MTS configuration. The MTS shares, however, the two TEU container search algorithm, which is needed when only one TEU container with the required destination is selected. In this case, to fill a two TEU or on FEU trailer with two TEU containers with the same destination a second TEU container is searched for.

The following Figure 2.5 shows the flow of containers from the generator to the MTS. As the trailers are not modelled in this simulation model, the loading of containers onto trailers is a task done by the TerminalEquipment. With the containers now in queues called MyMTSSelectContainerQ and

MyMTSLoadContainerQ, which hold containers that have been loaded onto the trailers with the first container of a trailers set in the MyMTSSelectContainerQ for easy identification the TerminalControl will check if there are MTS trucks available and will request an empty ride if the availability is zero.

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24

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2.5 The integer programming model

An integer-programming model has been made by Nieuwkoop [5] to determine the different ITT configurations. In these configurations the required number of transport vehicles is defined to fulfil the transport demand. For this research the transport demand that was defined using a generator designed by Jansen was used. This research has given the number of vehicles for each ITT

configuration consisting out of MTSs, AGVs, ALVs or Barges that are required to fulfil the ITT demand. Schroër has subsequently used these configurations in his simulation model and has concluded that the simulation model does not achieve the same level of ITT performance as was found achievable in with Nieuwkoop’s integer-programming model. The results of the simulation model showed that there would be a level of non-performance with containers arriving late when the numbers of vehicles that are determined with the integer-programming model are used.

In this research the choice has been to focus on the simulation model, this is due to the nature of the research question, which asks for an investigation and not an optimisation. Any conclusions of possible additional variables and requirements that have been found essential to represent a human operated MTS ITT system by this research can have implications for the integer programming model as this also is a representation of what a ITT system would look like and function in reality. To be accurate the correct assumptions have to be made, however to test assumptions and effects of the implementation of some variable or requirements on a system can be better and more efficiently tested on a simulation of that system instead of an optimisation model that tries to optimise certain parameters.

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3 MTS variables

The variables introduced by a MTS system to the simulation model, are a result of two elements of the system, the capacity of 10 TEU and the human operator. The capacity requires additional decisions to be made concerning pickup and delivery strategies, and to determine if trailer sets or even individual trailers are to be coupled and decoupled.

The human operators will introduce additional variables based on their requirements and will introduce an additional degree of unpredictability to the operational reliability.

3.1 Human operator variables

The variables introduced by the human operator originate from the operator’s requirements, which consists of both physical- and psychological requirements. Furthermore, some of these requirements are recognised by lawmakers, and have been implemented into European as well as the Dutch health and safety laws, collective work agreements and regulations, of which the European regulation (EG) 561/2006, [12] is the primary ruling as most national European regulations are subsidiaries of it. European regulation (EG) 561/2006 [12] regulates road transport and in particular the driver’s social legislation with working conditions being regulated by governing their driving times, breaks and rest periods.

As well as introducing human operator requirements into simulation models to more accurately represent systems where humans play an important role the integration of human factors, as it is most commonly referred to, can be of importance to find the balance between system control and that of operator decision-making. To accomplish a good integration the interface between operator and machine will also need to be modelled and tested.

The human operator is foremost the controller of the transport vehicle. However, one should ask what level of control of the operator is best. Should the operator be limited to driving from location to location as predetermined by the system, or can he be integrated into the control or decision-making process?

The integration of human operators into the control or decision-making structures of transport systems could have benefits and give added value to the use of human operators in a transport system in comparison to a fully automated one. However, for this research and the modification to the simulation model is chosen to implement only the human operators requirements, and not the

interaction between operator and control or investigate any integration of the two.

The requirements that can be identified as essential for the operator to be more accurately

represented in the ITT system that operates 24/7, include the implementation of work shifts which will require that several shift changes and breaks throughout the working day take place. That the ITT system operates 24/7 is clear as the terminals that contribute to the ITT system also operate 24/7 and will require the ITT system to do so as well.

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Fixed and legal requirements

3.1.1

These requirements are prescribed by the governing rules and regulations and are registered through collective work agreements and legislation and are therefore also legal requirements. These legal requirements are a combination of the requirements set by the European regulation (EG) 561/2006, [12] which is legislation concerning the transport of goods over the public road, health and safety laws, and collective work agreements which are a descendant of the national and European labour laws consecutively.

The European regulation (EC) No 561/2006 [12] describes the maximum allowable continuous hours of work, and the duration and frequency of breaks in the road transport sector. However, as the terminals on Maasvlakte 1 and 2 including the ‘interne baan’ road network are not part of the public road, the parties involved to establish and run an ITT network can deviate from the regulation’s restrictions. It is, ultimately, up to the parties involved to define working hours, scheduled breaks and other work related regulations within the applicable European and Dutch rules and regulations. One of the regulations to consider is the Dutch ‘Arbeidstijdenwet’, a law governing the working hours of employees and its translation in several collective work agreements of the container terminals on the Maasvlakte. Most, if not all terminals use the following time windows for work shift in continuous operations [13]–[15]:

1. Day shift, 07:15-15:30. 2. Afternoon shift, 11:30-19:45. 3. Evening shift, 15:15-23:30. 4. Night shift, 23:15-07:30.

For a 24/7 operation, which is applicable to the ITT system, the time windows start 15 minutes earlier allowing an overlap of 30 minutes for operators to change over.

Within the shifts there are time windows where half hour breaks are scheduled in such a way, that full continuous operation is maintained. Common time windows for breaks are as defined in the collective work agreement of APM Terminals in [13]:

1. Day shift, 11:00-13:30. 2. Afternoon shift, 15:15-17:15. 3. Evening shift, 18:30-21:00.

4. Night shift, 03:15-03:45, (extended window: 02:30-05:00)

The extended break window within the night shift can be used if the employer informs his personnel before the start of the shift and after doing so offers extra break of half an hour to the employee.

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The start time of each break within a time window should be predetermined so the personnel can be informed at least an hour before the start of each time window.

The most significant difference in the break times between the collective work agreements and the European Union’s regulations as found in [12], for road transport, is that the EU’s regulations prescribe that after a driving time of 4.5 hours a break of at least 45 minutes has to be taken. However, it is also allowed to split this break of 45 minutes into a break of at least 15 minutes followed by a break of at least 30 minutes.

As the ITT on the Maasvlakte 1 and 2 does not use public roads, it does not qualify as “carriage by road” as defined by the EU regulation in article 4 part (a) [12]. Furthermore, the MTS has a maximum speed of 30 kilometres per hour with which it does not exceed the maximum authorized speed of 40 kilometres per hour, that is stated in article 3 of the EU regulation [12] and is an exemption to the applicability of this regulation. The EU regulation is therefore not applicable or necessary and will not be included in the requirements or the resulting modifications to the simulation model.

Unpredictable and external variables

3.1.2

These variables are a result of unscheduled influences and have a varying degree of unpredictability. Unscheduled influences originating from the operator, for example, unscheduled breaks and sickness, as well as other circumstances that interrupt or halt operations, for example, breakdowns, accidents, extreme weather or security incidents can be considered as such.

It is, however, not necessary to introduce these variables into the simulation model if the goal of the simulation is not to test the effects of these specific unscheduled influences on system performance and recovery. Therefore, these variables and requirements to implement unpredictable and other external variables are not included in the modifications to the simulation model.

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3.2 MTS variables

Trailer coupling/decoupling

3.2.1

The coupling and decoupling of trailers is both an operational and a logistical problem. Operationally, coupling and decoupling of trailers or trailer sets of 5 will inherently require different handling operations at origins and destinations. If, for example, individual trailers are to be decoupled, it is necessary to evaluate whether it is technically possible to rearrange trailers by automatically or manually coupling and decoupling trailers and reversing more than one trailer at a time. These handling operations and their operability will therefore influence whether or not the coupling and decoupling of trailers is a viable option. Furthermore, the loading and unloading of trailers together with the facilities needed to do so will influence the practicability of certain strategies, for example, when trailers are not decoupled it will be necessary to unload a container from the MTS fast enough not to delay the MTS and, consequently, ITT operations. Decoupling will therefore be beneficial to act as a buffer between ITT and origin/destination operations.

Loading and unloading strategies

3.2.2

Pickup and delivery strategies are extensively researched and can be found in literature as pickup and delivery problems. According to Savelsbergh and Sol [16], a general pickup and delivery problem differentiates itself in comparison to general vehicle routing problems by several characteristics. The first and foremost is a transport task with either a single origin or starting point and several

destinations or multiple starting points and a single destination. Secondly, transport vehicles will have different starting points throughout the real time operation with transportation tasks derived from the real time transport demand scenarios.

3.3 Conclusions

For this research the strategy to couple/decouple and load/unload sets of trailers with containers that are to be transported to the same destination is advantageous as it has the advantage of the loading and unloading without the MTS truck having to wait and this also the way the Duinkerken et al. modelled the MTS in [17]. A further advantage, according to [18], is that the trailer sets can function as a buffer between terminal equipment and MTS transport.

Chapter 4 will go into greater detail as to which operational strategies can be made and describes which one is chosen and will be implemented into the simulation model.

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4 Operational strategies

By a further analysis of the MTS ITT configuration several details can be distinguished in addition to the elements representing the MTS ITT configuration in Schroër’s simulation model. These details can be separated in physical and theoretical characteristics and are closely linked. The physical layout of the MTS ITT configuration, as described in detail in Chapter 2.4, with a human operated traction engine or truck and up to 5 trailers capable of carrying 2 TEU each, results in a number of potential operational decisions to establish the possible strategies in day to day operation. These decisions can be split into loading and unloading operations that are dependent of the availability and usability of terminal operating equipment, for example stacking cranes or straddle carriers, and a dependence of different trailer coupling and decoupling possibilities, for example, the coupling and decoupling of sets of 5 to the coupling and decoupling of individual trailers.

4.1 Coupling and decoupling

Three possible strategies can be distinguished for the coupling and decoupling of MTS trailers. The first is to couple and decouple sets of trailers, whether of two or five trailers. This strategy will allow trailer sets to be used as a buffer; however, only if there is a sufficient number of trailers available. In addition, sets of trailers can be loaded and unloaded without the traction engine and the operator having to wait for terminal equipment. The MTS trucks can, when they arrive at a pickup location, simply couple a trailer set, ride to its destination and decouple. The number of possible pickup and delivery strategies for this strategy will be limited due to the decision to load and unload trailer sets prematurely to the arrival of the MTS traction engine, to single origin to single destination operation. This is the strategy used in Schroër’s simulation model where sets of five trailers are coupled and decoupled. However, the terminal has to load these sets with containers that all require to be transported to a single destination.

The second strategy for MTS trailer coupling and decoupling is to couple and decouple individual trailers. This strategy will require the MTS to be able to shunt trailers around to decouple or couple any trailer except the last one unless they have been loaded with containers that have the same destination. However, as the trailers have a capacity of two TEU, it will be necessary to load two TEU containers with the same destination, or one FEU onto one trailer to make the in situ unloading of one of the TEU containers at its destinations redundant.

The third strategy is not to couple and decouple at all and have MTS ride around with 5 trailers which, when arrived at their destination, will need to be unloaded after which new containers will need to be loaded before the MTS can continue. This requires terminal equipment to be at a reasonable standby time to be ready to load and unload a MTS without delaying it. In the worst case scenario, a MTS will have to wait the shortest time as possible for the terminal equipment to be available.

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4.2 Loading and Unloading

As a conclusion to the previous chapter it can be noted that the loading and unloading of containers is intertwined with the coupling and decoupling of trailers. Restricting the MTS not to couple or decouple trailers will result in the unloading and loading of containers in situ at their origin or destination respectively. Nonetheless, the decision to couple and decouple sets or individual trailers will result in the separation of the loading/unloading and coupling/decoupling operations where each one does not restrict the other in terms of possible strategies. The exemption of this derestriction occurs if the coupling and decoupling of sets of five trailers is considered, in this case only one coupling and decoupling strategy remains, which means to couple and decouple sets of 5 trailers.

Possible strategies

4.2.1

If shunting and effective loading and unloading of containers is possible, it will replace in situ loading and unloading completely. In practice the deliberation will have to be made based on the ease and time lost of each loading and unloading and coupling and decoupling strategy.

Both shunting operations and the loading and unloading of trailers in situ will require the driver and traction unit to stay stationary, thus not being able to fulfil new transport tasks. The coupling and decoupling of sets of trailers and loading and unloading them if the terminal has equipment ready to do so will allow the MTS driver to operate fully on transporting containers resulting in the maximum possible utilization of personnel and equipment. This strategy will, however, require a larger number of MTS trailers as these now function as a buffer between the stack and the ITT system.

A further consideration is the loading rate of the MTS, as it is desired that the MTS should be loaded to or close to their maximum capacity of 10 TEU, in order for it to transport the maximum number of containers possible and fully utilising its capacity. However, the need for a container or a number of containers to be transported by the ITT system can be categorized by urgency, or by the number of containers with the same destination. Urgent containers will have to be loaded and transported as soon as possible, whereas non-urgent containers can be held longer on a terminal until there are enough containers with the same destination to fill a MTS to its maximum capacity or close to it.

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4.3 Pickup and delivery of containers

Without the limitations on the type and number of pick-up and delivery strategies that can be used, most pick-up and delivery strategies can be described according to Savelsvergh and Sol [16], as either a Pickup and Delivery Problem, where transport takes place between single origins and single

destinations or a Vehicle Routing Problem, where transport takes place from multiple origins to a single destinations, or from multiple destinations to a single origin.

Pickup and Delivery Problem

4.3.1

When the ITT system is considered as a Pickup and Delivery Problem, described by Savelsvergh and Sol [16] as having a single origin and a single destination, the different strategies to couple/decouple or load/unload the trailers that can be used are not restricted. To decide which is the best

loading/unloading and coupling/decoupling strategy for this problem, the minimum return times of each strategy to load/unload or to couple/decouple sets of trailers of the MTS at the origin or destination will need to be compared.

The time that is required for the loading and unloading of containers has been established by Schroër [2] as exponentially distributed with a mean of 3 or 4 minutes depending on the equipment that is used. The coupling and decoupling of trailers is fixed at ½ minute, unfortunately process is not described in further detail in Schroër’s report [2]. Furthermore, only the time that is required to couple the MTS truck to a trailer or trailer set is mentioned and not that of the coupling and decoupling of individual trailers.

The coupling and decoupling of individual trailers is something that has been researched and mainly for the complexity of the reversing process. When a MTS truck is required to reverse with more than 1 or 2 trailers it becomes very difficult, as there is a lack of directional control of the trailers. Thus the strategy to couple and decouple individual trailers would require advanced control technology which is according to Morales et al in [19] a nonlinear control problem. This strategy is therefore not common and would require a re-design and further development of current MTS container transport systems. The only other possibility is that terminal equipment is used to fulfil this task. However, at the time of writing no literature has been found that specifies and researches the use of terminal equipment to shunt MTS trailers. Furthermore, the use of terminal equipment would most likely also require advanced control systems for the equipment to perform this task, which it is not designed for.

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Vehicle Routing Problem

4.3.2

Considering the ITT system as a Vehicle Routing Problem, described by Savelsvergh and Sol [16] as having multiple destination and a single origin or vice versa,will result in it influencing the chosen strategies to either couple/decouple or load/unload trailers. The coupling and decoupling of trailers will be restricted as in some cases the set of 5 trailers behind a MTS will have different destinations and will necessitate the need to couple and decouple individual trailers. This results in the need to shunt and rearrange the trailers behind a MTS at a pickup and or delivery location. This process might require trailers with different destinations, which are coupled to a MTS, but are decoupled as part of the shunting/rearrangement process, to be recoupled as well as any new trailers that are to be picked up.

The strategy not to couple and decouple trailers will result in the need to load and unload trailers in situ. Again the minimum return time to unload containers arriving at their destination and to load containers that are to be transported by the MTS will be the determining factor whether this strategy is beneficial for the couple and decouple trailers or sets of trailers strategy.

Conclusion

4.3.3

To conclude, this research and the modifications of the simulation model will use the strategy to couple and decouple trailer sets consisting of 5 trailers and does not consider individual trailers as the challenges that this would introduce, with shunting and rearranging, in a real world application are not realistic. Furthermore, the simulation model has not been set up with more advanced strategies in mind and to implement them would require a complete rewrite or the creation of an entirely new simulation model.

The strategy not to couple or decouple trailers and have the MTS ride fixed with a set of trailers is not chosen as a viable option due to the relatively long load and unload times, which would delay the MTS trucks as they wait to be loaded. Furthermore, the nature of the MTS as described by Duinkerken et al [17] as “batch” type, which is due to the large capacity will result in subsequent challenges to utilize that capacity to its full extent. The strategy to decouple the MTS trucks from the trailers has the best possible change to utilize the capacity of the MTS as the trailers now function as a buffer between the terminal equipment, and the ITT system, which allows the terminals to load containers onto the trailers as optimal as possible and without delaying the MTS trucks. This strategy is therefore chosen and is implemented into the simulation model.