Airport Slot Allocation Processes. A heuristic approach

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FACULDADE DE

ENGENHARIA DA

UNIVERSIDADE DO

PORTO

Airport Slot Allocation Processes

Rafael Filipe dos Santos

Mestrado Integrado em Engenharia Eletrotécnica e de Computadores Supervisor: Maria Antónia da Silva Lopes de Carravilla

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Airport Slot Allocation Processes

Rafael Filipe dos Santos

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Resumo

Hoje em dia aeroportos encaram imensos casos de congestionamento, resultando em atrasos de voos, levando assim a tentar encontrar uma solução que permita mitigar este problema. Uma das soluções mais adoptadas para mitigar congestionamento de aeroportos é utilizando o processo de alocação de slots da International Air Transport Association (IATA). Este processo consiste em alocar horários de voos de acordo com certas regras e com base nos pedidos feitos pelas companhias aéreas. Contudo, é um processo que é extremamente difícil de optimizar devido a restrições impostas por aeroportos, levando a casos em que existe uma discrepância enorme entre horários requisitados e horários alocados.

Esta tese consiste em encontrar uma forma optimizada the resolver o problema de alocação de slots em aeroportos. O principal desafio neste problema é encontrar um método capaz de alcançar um solução admissível, que siga maior parte das guidelines impostas pela IATA.

O projeto desenvolvido começa com uma revisão literária de maneira a adquirir a informação necessária de como o processo de alocação de slots é realizado tendo em conta as regras da IATA. Uma análise meticulosa é feita em ordem a perceber quais são as regras prioritárias principais e como essas influenciam o processo de alocação de slots.

Uma análise da congestão de aeroportos é também feita de maneira a perceber como surgem atrasos e como diferentes maneiras podem ser tomadas de maneira a mitigar esses atrasos. Uma análise cuidadosa teve de ser feita visto a tese focar-se numa abordagem em particular, e então um bom entendimento de todos os processos involvidos nessa abordagem tem de ser garantido de maneira a encontrar sucesso na solução apresentada.

Visto que o problema é extremamente complicado, vários autores já tentaram encontrar soluções por métodos exatos, de maneira a alcançarem soluções ótimas, no entanto apenas provaram terem sucesso em aeroportos de menor dimensão. Face a este problema, a solução definida para esta tese foi a de implementação de um sistema de apoio à decisão, devido ao facto de que o processo de alocação de slots necessitar de tomadas de decisão importantes para garantir satisfação dos pedidos de voos. Essa solução consiste num Sistema de Apoio à Decisão que permite avaliar o cumpri-mento das restrições à medida que uma solução é construída. O processo the implementação necessitou de uma análise da informação fornecida a coordenadores de slot, de maneira a perceber quais seriam os inputs que o sistema teria de usar no seu método. De seguida foi necessário de-cidir uma plataforma de implementação que garantisse que toda a informação estivesse guardade a apresentada ao utilizador numa interface intuitiva e de fácil compreensão.

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Abstract

This thesis consists in finding an optimal way to solve slot allocation problems in airports. The main challenge to this problem is to find a method that is capable of finding an optimal or close-to optimal solution that follows most of the International Air Transport Association (IATA) guide-lines.

Nowadays airports face immense cases of congestion resulting in flight delays which lead to finding solution to mitigate this issue.

The developed project starts with a literature review in order to acquire the information needed to understand how the slot allocation process is made in accordance to the IATA rules. A thorough analysis is made in order to understand what are the key priority rules established and how the influence the slot allocation process.

An analysis of the airports congestion is also made to understand how delays appear and how can different approaches can be taken into account in order to mitigate them. Careful analysis must be made since the thesis focus in one approach in particular and so a good understanding of all the processes involved in the selected approach has to be ensured to have success in the solution presented.

The defined solution for the thesis was that of a decision support system implementation, due to the slot allocation process being one that requires important decision making to satisfy as op-timally as possible flight requests. The process of implementation first required an analysis of the information provided to slot coordinators to understand what were the inputs that the decision support system would have to use in the method. Secondly, it was needed to decide an imple-mentation platform for the decision support system in order to have all the information stored and presented in a user interface intuitive for the user.

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Acknowledgements

First and foremost i would like to thank my parents for all the support and love they have given me throughout the years, for investing in me and my education to ensure a solid basis for my future. I also thank my sister, she has been accompanying me ever since she was born and supporting me through the good and bad times.

I would also like to thank my supervisor Maria Antónia Carravilla for always giving me sup-port in our meetings, approving or disapproving of my ideas, and always maintaining a friendly ambience in order to ensure my calmness through stressful times. A really big thanks for all the help.

Finally, to all my friends that supported me throughout my time in college, the ones that were close to me already from before and the ones close to me now, a really big thank you to all, you always supported me and incentivized me to keep working and finish this work. I hope i also did a good job in helping you in the same situations you helped me.

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“You build on failure. Use it as a stepping stone and close the door on the past. Don’t try to forget the mistakes, but don’t dwell on it.”

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List of Figures

2.1 Slot Allocation Process workflow by WSG IATA . . . 7

2.2 Airport Level classification by WSG IATA . . . 8

2.3 Slot Allocation Process (extracted fromRanieri and Alsina(2014)) . . . 10

2.4 PDC SCORE Software (extracted from (PDC Aviation,2018)) . . . 12

2.5 Geographical distribution of the EUACA members (extracted from (European Air-port Coordinators Association,2018)) . . . 13

2.6 Level 2 and 3 Airports Worldwide (extracted from (International Air Transport Association,2017)) . . . 14

3.1 Declared Capacities of the Porto Airport (extracted from (International Air Trans-port Association,2017)) . . . 16

3.2 LOS Guidelines (extracted from (IATA Level of Service,2017)) . . . 18

3.3 Zografos model (extracted from (Nuno Antunes Ribeiro,2016)) . . . 23

3.4 Zografos model Sets and Parameters (extracted from (Nuno Antunes Ribeiro,2016)) 24 3.5 Pyrgiotis model (extracted from (Nuno Antunes Ribeiro,2016)) . . . 25

3.6 Pyrgiotis model Sets and Parameters (extracted from (Nuno Antunes Ribeiro,2016)) 26 4.1 Madeira airport declared capacities (extracted from (ANA Coordenação de Slots, 2018)) . . . 33

4.2 Lisboa airport declared capacities (extracted from (ANA Coordenação de Slots, 2018)) . . . 33

4.3 Operational Time (calculated in days) . . . 37

4.4 Frequency of Operation . . . 37

4.5 Excel Sorting Window . . . 38

4.6 Excel Sorting Result . . . 38

4.7 Initial Schedule Allocation Result . . . 39

4.8 Surpassed Capacities . . . 39

4.9 Surpassed Capacities . . . 40

4.10 Total Schedule Shifts . . . 40

4.11 Maximum Index Calculated in Initial Allocation Table . . . 41

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List of Tables

2.1 Heathrow slot valuations from reported trades 1998 to 2013 (Heathrow,2013) . . 6

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Abreviaturas e Símbolos

IATA International Air Transport Association WSG Worldwide Slot Guidelines

EUACA European Airport Coordinators Association LOS Level of Service

DSS Decision Support System WWW World Wide Web

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Chapter 1

Introduction

Airlines are one of the most used methods of transportation nowadays. Since its growing industry, the need for air transportation has had a significant augmentation therefore it gets extremely diffi-cult for the airports to increase their capacity leading to immense cases of congestion and delays causing high costs for airports, airlines and passengers alike.

Knowing this, airports need to have a solution to help them mitigate some of these issues. One of the possible solutions for this problem is the expansion of the airport area, allowing to physically increase capacities. Another solution could be the implementation of new air traffic management technologies. However, both these solutions, for how intuitive they can be, can also be extremely time consuming, investment-intensive and also, for the case of airport expansion, very unlikely due to urban localization.

An alternative for these solutions should be an approach through demand management mea-sures that can constrain flight demands to minimize the expected exceeded airport capacity.

The International Air Transport Association (IATA) slot allocation is the most used method of demand management control for the busiest airports outside of the United States (around 300 airports worldwide). The IATA slot allocation is based on schedule coordination, which means that the process allocates requests into different time "slots" based on the capacity provided by the airports. Each airport presents to the coordinators their declared capacity, which determines the number of slots available per unit of time, consisting in blocks of 60 and 15 minutes. Based on the IATA guidelines, slot coordinators must allocate slots accordingly following the priorities established, that is, first and foremost, the flights that belong to series of flights. These are flights that occur at least five times over a season, on the same day or days of the week and at the same time of the day. Among these series of flights there are other three priorities that the IATA guidelines establish for proper allocating. First, slot coordinators must allocate flights that hold historic rights. Historic rights are given to airlines that operated at least 80% of the time in the previous season. Second, they must allocate historic flights that requested a change in their request and finally, 50% of the remaining available slots must be to new entrants.

Regarding the priorities referred above, there are many more specifications that the IATA guidelines establish, turning the process of slot allocation into a complex problem. To aid slot

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2 Introduction

coordinators in this process, there are specialized software packages that provide instantaneous information about the priority of a flight in a slot request and the availability of slots for that flight. However, slot requests are often treated in a first-come-first-served manner, which leads to many schedule adjustments resulting in a high number of delays.

Recently, some optimization models have surged with the purpose of further aiding slot coor-dinators in their process of slot allocation. Further explanation of these models will be described in the adequate chapter, introducing afterwards the full explanation of the method used in this thesis and its results.

1.1 Motivation

For years airlines have been one of the most viable means of transportation for people, cargo and others. Having the least amount of delays to ensure satisfaction amongst passengers and airlines is borderline essential to the market. Even though there are some optimization models that help in the slot allocation process to ensure less delays, future improvements can be made to reach even better solutions to those existing.

Therefore, the motivation for this work is to define a decision support system that accommo-dates the IATA guidelines and further helps in achieving the optimal solution for slot allocation.

1.2 Research Problem

The problem consists in the appropriate slot allocation minimizing the delays while following as thoroughly as possible the IATA guidelines and keeping in mind the airport restrictions when it comes to slot capacity and terminal capacity. According to this, the following questions were formulated:

• How to have all the information needed for the slot coordinator to make a decision on how to allocate slots more efficiently?

To aid the slot coordinator into making the most optimal decision while allocating slot re-quests, the idea of a decision support system surged. It can serve as an efficient and easy to use tool that in the end gives the slot coordinator a possible solution within the restrictions provided by the airport and the IATA guidelines.

• In what way could a decision support system help the slot allocation process?

With the help of a decision support system, the slot coordinator can have a wide range of view when it comes to have all the information needed for a slot allocation. This means that while analyzing all the requests, the slot coordinator can easily make changes and see how it will affect the final result, making changes accordingly if the result is not adequate.

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1.3 Project Goals 3

1.3 Project Goals

The main objectives for this thesis are:

• Study and detect the major problems in the slot allocation process.

• Create a decision support system to aid slot coordinators achieve a possible solution to this problem.

1.4 Methodology

The methodology followed in this thesis consisted in the study of various methods used in slot allocation process and airport capacities. Afterwards, with the information previously researched and studied upon, a fictional airport was created and used as a case study to demonstrate how the solution presented in the thesis can help achieve a decision as a possible solution in slot allocation.

1.5 Document Structure

This dissertation is organized in five chapters. Chapter 1 consists in the introduction in which are presented the motivation of the developed work, the research problems and a general overview of the project. Chapter 2 presents the literature overview, which includes slot definition, the IATA guidelines and slot allocation, and also the software used by slot coordinators in the allocation pro-cess. Chapter 3 details the airports slots and capacities, showing how exceeding of these restraints can lead to airport congestion, and the consequences of such, and it also details some existing optimization models that handle schedule management. Chapter 4 presents the proposed solution for the problem of the thesis and its results, analyzing how it can aid the slot allocation process and how it can be further improved. Finally in Chapter 5 the final thoughts and future work are

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Chapter 2

Literature Review

This chapter presents a review of the Worldwide Slot Guidelines (WSG) published by the Interna-tional Air Transport Association (IATA), as well as some existing optimization models in the slot allocation process. The main purpose of the guidelines is to indicate a set of rules that can be used by slot coordinators in the slot allocation process.

2.1 IATA Worldwide Slot Guidelines

The Worldwide Slot Guidelines published by the IATA is a document in which is provided a set of standards for the slot coordinator at coordinated airports and planned operations at facilitated airports to aid in the management of said facilities. The separation between coordinated airports and facilitated airports is made depending in the amount of demands made by airlines. If the demands surpass the available infrastructure, the airport is categorized as a level 3 airport, resulting in the application of a slot allocation method with historic rights to ensure slot distribution is made efficiently, minimizing the amount of delays that will inevitably occur. When demands are closely reaching airport capacity but don’t surpass it, the airport reaches a level 2 category, where coordination is needed to ensure that demands do not exceed the provided capacities. As described in the introduction to this thesis, there are around 300 airports that follow the IATA slot allocation method. According to a list provided by the IATA, in the winter season of 2017 there was a total number of 122 level 2 airports and a total of 161 level 3 airports.

The standards provided by these guidelines have been developed since 1974 and are the re-sult of several agreements between airlines and airport coordinators and facilitators conre-sultation. Since it was mutual consultation, the guidelines represent the best practice for coordination and management for airport slots. The term coordination is used to refer the allocation of slots by slots coordinators or the approval of planned operations by facilitators.

Even though the principles and processes indicated in the guidelines document is meant to be the best practice for worldwide application there is the possibility of some States and Regions to have regulations controlling some of these issues. In such cases, the regulations established by those regions will have precedence over the standards presented in the guidelines.

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6 Literature Review

The WSG is presented in a way to induce easy access to the standards it provides that support the allocation and management of airport slots at congested airports. It is a document that is in constant revision to allow itself to be up to date with the industry and regulatory changes. Overseen by the IATA Join Slot Advisory Group (JSAG), a group formed by an equal number of airlines and airport coordinators, the document undergoes changes resulted by the agreement of all the proposals the JSAG concludes. After an agreement in the document changes, the Head of Delegation of the Slot Conference must endorse them to ensure that no new or changed policy will be introduced by any airline, coordinator or IATA.

2.2 Slots and the IATA Slot Allocation Process

2.2.1 Slot Definition

A landing slot, or airport slot, is a permission given by the coordinator in charge for a planned operation to use all of an airport infrastructure necessary for arrivals and departures at an airport on a specific requested date and time. For level 3 airports, where demands exceed the airport capacities, slot allocation is an extremely important process to ensure the minimum delays possible in flights. Due to slot allocation, these landing slots can present commercial value and such can be traded between airlines. As demand exceed supply, slot trading has become more and more usual in the business. Table2.1demonstrates how slot trading has evolved in the past 20 years.

Table 2.1: Heathrow slot valuations from reported trades 1998 to 2013 (Heathrow,2013) Year Acquirer Vendor Number of daily

slots pairs Sum paid (£M)

Value per slot pair (£M) 1998 BA Air UK 4 15.6 3.9 2002 BA BA Connect 5 13 2.6 2002 BA SN Brussels 7 27.5 3.9 2003 BA SWISS 8 22.5 2.8 2003 BA United 2 12 6 2004 Virgin Flybe 4 20 5 2004 Qantas Flybe 2 20 10 2006 BA BWIA 1 5 5 2007 BA Malev 2 7 3.5 2007 BA BA 7.3 30 4.1

2007 Virgin Air Jamaica 1 5.1 5.1

2007 BMI 77.7 770 9.9 2007 unknown Alitalia 3 67 22.3 2008 Continental GB Airways/Alitalia/ Air France 4 104.5 26.1 2013 Delta unknown 2 30.8 15.4 2013 Etihad Jet 3 46.2 15.4

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2.2 Slots and the IATA Slot Allocation Process 7

2.2.2 IATA Slot Allocation Process

The slot allocation process is the mechanism used at congested airports to try and maximize the efficient use of airport infrastructure using proper allocation of landing slots. This process relies on the coordinator to make the minimal changes possible in the schedules requested by airlines to minimize the number of flights scheduled at peak hours, distributing them more evenly throughout the day.

Stated in the WSG IATA rules, any aircraft that intends to arrive or depart in an airport needs to have a slot allocated for that purpose. The slot represents the permission given by the airport to the airline to fully utilize the airport infrastructure necessary for the movement of the aircraft. Every season, a large number of airport slots are requested by several airlines, and slot coordinators have the function of guaranteeing that each request is allocated properly, ensuring that none surpasses the airport declared capacities.

The process of allocation occurs every season, winter and summer, and begins one year before operations. When an airport is designated as slot coordinated, the airport should perform a demand and capacity analysis to provide the airport declared capacities to the slot coordinator in order to be used in the slot allocation process. Afterwards the slot coordinator begins the initial slot allocation of the requests made by the airlines, taking into account the priorities set by the IATA guidelines and the declared capacities of the airport. Before each season starts the IATA Slot Conference takes place where airlines representatives, slot coordinators and other interested parties discuss and make adjustments to the initial slot allocation. After the conference, airlines can still make some small adjustments to the initial slot allocation and also trade slots with other airlines. Slots that won’t be used by airlines should be returned so that others flights can use those slots. Figure2.1

illustrates in a basic way the process flow of the IATA Slot Allocation Process.

Figure 2.1: Slot Allocation Process workflow by WSG IATA

2.2.3 Airport Level Classification

The level of congestion of each airport is classified by the WSG depending on the demands made and if those demands surpass airports capacities.

• Level 1 Airport:

A Level 1 airport is one where capacity of the airport infrastructure is generally adequate to meet demands of airport users at all times.

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8 Literature Review

agent if one is appointed. Operations at Level 1 airports are not discussed at the SC since that in these cases the process of slot allocation is not required.

A Level 2 airport is one where the potential for congestion exists during some time of the day, week or season. Schedule adjustments mutually agreed between the airline and the facilitator can resolve the issue of congestion. These airports are also known as facilitated airports where a facilitator is appointed to follow the guidelines and aid airlines in selecting alternative solutions to arrivals and departures times when congestion is likely to occur. The facilitator must be independent and act in a neutral, transparent and non-discriminatory way. Airlines should be prepared to accept an alternative time if offered by the facilitator to avoid exceeding the coordination parameters, otherwise the airport may need to consider changing to Level 3.

Finally, a Level 3 airport is one where demands exceed airport’s capacity during the relevant period and there is no possible way through expansion or voluntary schedule adjustments to meet demands in the short term. These airports are also designated as coordinated airports, where a coordinator is appointed to perform the slot allocation process in the most neutral, transparent and non-discriminatory way. Coordinators must have sufficient time, resources and expertise to provide coordination services in accordance to these guidelines, as well as software tools capable of performing functions necessary to comply with the WSG and any local guidelines. Airlines operating or planning to operate at a Level 3 airport must be allocated a slot by the coordinator before operating at that airport. Coordinators have to allocate slots accordingly to the capacities provided by the airports and following the rules stated by the WSG. They also should attend every Slot Allocation Conferences. After the process of slot allocation is completed, coordinators must continue to monitor the use of airport slots in order to detect any anomaly in their planned use.

The airports of Level 3 are the type of airports that are the focus of this thesis.

There are currently close to 200 Level 3 airports worldwide, in which 3 of 5 Portugal airports are included in that category, those being the Funchal, Lisbon and Porto airports. As can be seen in Figure2.2.

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2.2.4 Initial Slot Allocation

The process of slot allocation initiates after the end of the IATA schedule submissions deadline. This is when the airlines are requested to submit their desired schedules of operation. Typically, the process of initial slot allocation is applied to series of slots, however, ad hoc flights and other services can also be allocated during this time, even thought they are allocated only after the series of slots and are not limited by the deadline.

The WSG defines series of slots as a sequence of at least 5 slots requested for the same time of the day, on the same day of the week, distributed regularly in the same season, and allocated in that way or, if not possible, allocated at approximately the same time. This helps to capture the airlines regular flights, and give them priority accordingly.

During the initial slot allocation process, slot coordinators must allocate slot requests taking in account the declared capacities. Due to capacity limitations, coordinators might have to reschedule or even reject a certain number of slot requests. The rules presented in the WSG IATA define the priority that should be used by slot coordinators during the initial slot allocation.

The first slot allocation rule established by the WSG IATA is the historic precedence rule. This definition states that an airport as historic rights if a series of slots operated at least 80% of the time in the previous equivalent season (summer or winter). This rule allows airlines to keep their regular flights without being threatened by changes made at the start of a season. Even thought this helps airlines keeping their regular flights throughout different seasons it doesn’t mean that it is a guaranteed reservation of a slot, since the use-it-or-lose-it rule, or the 80-20 rule, states that the slot must be used more than 80% of it’s established time. Also, misconducted use of the slot can result in the loss of historic rights. Slots must be in constant monitoring by the slot coordinator to ensure that they are not being misused of their purpose. Non-utilization of historic slots can be justified by unforeseeable or unavoidable causes. The acceptance of the justification is up to the slot coordinator.

After historic slots have been allocated, the second priority is the changes to historic slots. These are flights that already hold an historic slot but due to operational reasons, a change in time or aircraft type is required, therefor a request for change in the slot is made. If the requested slot cannot be allocated, the coordinator must inform the airline about the reasons of why a change can’t be made and indicate an alternative solution. If an alternative solution is not found by the coordinator, or rejected by the airline, the slot is rejected.

The third and last main priority is the allocation of new entrants and rejected slots. For this purpose, the slot coordinator creates a slot pool in which 50% of this pool must be allocated to new entrants, unless the amount of new entrants is less than 50%. The remaining slots are allocated to the other requests. The following image extracted from a working paper published in 2014 (Ranieri and Alsina, 2014), illustrates the slot allocation process in a simple way. The working paper also refers to priority rule called Public Service Obligations (PSO). The PSO are operations

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10 Literature Review

Figure 2.3: Slot Allocation Process (extracted fromRanieri and Alsina(2014))

Within each priority mentioned above, a request to extend any existing operation has priority over any new request. Other criteria that are established in the WSG IATA, in case slots cannot be allocated based on the above-mentioned priority rules, are:

• Effective Period of Operation: The schedule which represents a longer effective period of operation in the same season should have priority.

• Type of Service and Market: The balance of different types of services and markets should be considered as a priority.

• Competition: Coordinators should try to ensure that due account is taken of competitive factors in the allocation of available slots.

• Curfews: When a curfew creates a slot problem elsewhere, priority should be given to the airline whose schedule is afflicted by the curfew.

• Requirements of the Travelling Public and Other Users: Coordinators must, at their best, ensure that the needs of the travelling public and shippers are met as far as possible. • Frequency of Operation: Higher frequency can be considered more valuable, but should

not itself imply as higher priority for slot allocation.

• Local Guidelines: Local guidelines must be taken into account by the coordinator should they exist, only if approved by the Coordination Committee or equivalent entity.

2.2.5 IATA Slot Conference

The IATA Slot Conference is a seasonal conference that takes place in November and June, exactly 3 months before a season starts. In this conference, airports and airlines representatives can make the schedules adjustments necessary to the upcoming winter and summer seasons. The main purpose is to create a time frame where slot coordinators and airlines adjust schedules regarding

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the alternatives presented during the initial slot allocation, or exchange slots between airlines. All interested airlines and slot coordinators must attend the IATA SC, making the conference the best place for airlines to perform the adjustments necessary to its schedules. particularly if there is more than one airport affected.

2.2.6 Slot Returns and Adjustments

When an IATA slot conference finishes, airlines continue their scheduling process performing schedule adjustments accordingly. These adjustments are important to optimize airlines schedules to their needs. Schedule adjustments can be made in four different ways.

1. Airlines can change how they use the service of their slots, by transferring the intent service from on slot to another, as long as the slot is operated by the same airline, for example, changing the fight number.

2. Slots can be exchanged on a one-for-one basis between airlines, this is known as secondary trading. If these exchanges involve any newly allocated slots, the coordinators have the right to refuse as long as it is justified that it does not improve the operating position of that airline.

3. Airlines can transfer slots between parent and subsidiary companies. In such cases, the transfer is only permitted if the slots have been operated for two equivalent seasons. This rule is to prevent airlines from taking advantage of enhanced priorities.

4. Shared operations are allowed so that slots held by one airline can be used by other airlines. This mechanism is used so that airlines can retain historic rights of slots that they do not intend to use in that season.

Airlines should return any slots that they do not intend to use, allowing more opportunities for successful slot reallocation by coordinators and airlines. The slot return date is dated about two months before the season starts. Any late slot returns are considered as unused, minimizing the opportunity for an airline to achieve historic rights to their slots.

2.2.7 Slot Allocation Software

As described previously, the slot allocation process is driven by several rules and constraints. To ensure their right application, slot coordinators use a specialized software to aid their activity (e.g., PDC SCORE).

The software provides instantaneous information about the slot request, such has the priority class of each flight, the availability of slots, the violations it causes with the declared capacities, concerning runway, apron and terminal capacities. It can also take into account regulatory con-straints, such as night curfews and noise restrictions. The only downside is that software requires that slot coordinators organize the requests, but since slot requests are typically treated by slot

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co-12 Literature Review

that comes after the previous may be allocated in a non optimal way, even though it may have a higher priority.

When a request slot time is not available, the nearest slot, be it after or before the requested one, is calculated automatically and an offer is generated to the airline, which can accept or refuse the offer.

Figure 2.4: PDC SCORE Software (extracted from (PDC Aviation,2018))

As it can be seen in Figure2.4, the software provides a very complex layout with all schedule and request information to aid the slot coordinator in the process of slot allocation. The image provided by the website isn’t clear enough to understand if the software is intuitive enough for the slot coordinator to have all information presented at the same time to obtain a solution that can be better than the calculated one offered by the software.

2.2.8 Slot Allocation Worldwide

Nowadays the IATA guidelines are a standard adopted by a vast number of congested airports worldwide, even though they are not legally enforced by any means. According to IATA, around 300 airports are being coordinated worldwide in the last couple of years. A detailed excel file provided by the IATA shows exactly the number of level 2 and level 3 classified airports around the world, in which, during the winter season of 2017, 122 airports were classified as level 2, and 161 airports were classified as level 3. Europe is the most prominent region, with a total of 76 level 2 airports, and 75 level 3 airports, which represents close to 54% of the total airports classified by the IATA at that season as shown in Figure2.5.

The European Airport Coordinators Association (EUACA) provides a list of all constrained airports in the European region. The EUACA is the association responsible for allocation of slots or advising schedule timings in more than 100 airports in Europe. It is constituted by 20 European coordinators and schedule facilitators and they follow the EU Regulation 95/93 (EEC,1993) and

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its amendments, Regulation 894/2002, Regulation 1554/2003, Regulation 793/204 and Regulation 545/2009.

These regulations basically retain the key features of the IATA allocation process. The biggest difference between the two mechanisms is that the IATA relies on mutual agreements and the EU regulation is a binding legal framework (Langner, S. J.,1996).

Figure 2.5: Geographical distribution of the EUACA members (extracted from (European Airport Coordinators Association,2018))

Meanwhile, in the USA slots are allocated on a first-come, first-served basis. The only ex-ceptions to this method are at 5 slots-constrained airports in which two are classified as level 3 by IATA, the John F. Kennedy International Airport (JFK) and the Newark Liberty International Airport (EWR). Other airports in the USA are considered level 2.

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14 Literature Review

Figure 2.6: Level 2 and 3 Airports Worldwide (extracted from (International Air Transport Asso-ciation,2017))

As can be noted in the above Figures, the IATA rules of slot allocation are present in a vast number of airport worldwide, dominating mostly the European region.

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Chapter 3

Capacities and Existing Optimization

Models

In this chapter, the definition of airport capacities will be demonstrated, as well as how they can influence airport congestion. It will also be discussed some of the existing optimization models and how these aid in slot allocation to prevent some of the congestion.

3.1 Airport Capacities

Airports are usually divided into two subsystems, the landside and airside areas. Landside in-clude areas such as terminal buildings, check-in, parking lots, public transport railway stations and access roads. Airside areas include, runways, taxiways and aprons. These systems exist to accommodate different types of entities, for example, runways must be able to handle aircrafts landing and taking off and terminal buildings have to ensure passengers and/or cargo flow. Capac-ities are then defined by the ability that the airport has to handle these different types of entCapac-ities.

When analyzing airport capacities, the runway infrastructure is usually the main cause of bottleneck in an airport system. This is a common issue, since it is extremely difficult, time-consuming and expensive to increase their available capacity at major airports due to acquisition of additional land, infrastructure cost and environmental impacts, forcing processes of approval that are usually extremely long and difficult. Commonly it is easier to adjust the capacity of other airports elements, such as terminals and aprons, in order to equal the capacity of the runway sys-tem.

Airport capacity is usually defined as the number of aircraft movements that can be operated per unit of time at an airport. However, there are other elements, such as passenger flow, that must be taken into account to evaluate the operating capabilities of the airport.

According to the literature De Neufville and Odoni(2013) there are two accepted basic def-initions of capacity. One of them is practical capacity, which considers a certain level of service when computing capacity, and the other one is throughput capacity which does not take this into account and instead represents the full capacity of the airport. Additionally, capacity may also be

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16 Capacities and Existing Optimization Models

defined as static or dynamic. Static usually refers to the maximum number of entities that can be accommodated simultaneously at the airport, while dynamic represent the maximum service rate, i.e. the number of entities that can be served in a given amount of time under different conditions of constant demand for service.

Taking into account the different definitions of capacity there are several ways of presenting airport capacity, those being:

• Sustained Capacity:

It is the number of movements per hour that can be sustained over a period of several hours. Usually throughput capacity cannot be sustained for more than one or two hours and that is why sustained capacity is typically considered a more realistic target since airports are often subject to heavy demands for several hours or entire days.

• Declared Capacity:

It is defined as the number of movements per hour that an airport can accommodate at a reasonable level of service, typically using delays as a service indicator. As mentioned in Chapter2, during the initial slot allocation process, declared capacities must be given to slot coordinators.

As shown in Figure 3.1, the declared capacities of an airport are usually present in a table format, stating capacities for total movements in block of 60 and 15 minutes, as well as capacities for independent arrival and departures for 60 and 15 minutes, apron capacity and total passengers flow per 60 minutes.

Figure 3.1: Declared Capacities of the Porto Airport (extracted from (International Air Transport Association,2017))

The values calculated for these types of capacities are usually considering that 50% of the total movements are arrivals and the other 50% departures, which may not be extremely realistic since most of the requested movements can be unpredictable and only of one type, be it arrival, departure or a combination of both. Estimating correctly airport capacities is essential to airport planning and management. If airport capacity is overestimated, the demand may exceed the real capacities of the airport, resulting in multiple cases of over-scheduling, resulting in delays, congestion and

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3.1 Airport Capacities 17

low service level. On the other hand, if airport capacity is underestimated it may lead to the rejection of newly competitors and the unnecessary refusal of flights.

3.1.1 Landside Capacities

An airport landside system is responsible for the smooth flow of passengers in arrivals and de-partures within the airport. It is usually divided into two subsystems, the airport ground system, i.e. the links and nodes that connect to the roads, railways, etc., enabling transportation from the airport to the outside world (and vice-versa); and the terminal building which provides a set of services that enable the safe transition from the ground to the air transport method.

Landside elements can be divided into 3 specific categories (Hom and Orman):

1. Processing elements, which are responsible for processing passengers and their baggage in the airport.

2. Holding elements, which are responsible for having holding zones where passengers can wait for flight boarding or check-ins.

3. Flow elements, that ensure safe passage for passengers to move among other landside ele-ments or to the airport terminal.

The total landside capacity is determined from the individual capacities that each of these categories represent, also depending on the level of service required by airport managers. Level of service can be considered as a measure which represents the passenger’s satisfaction with the quality and service conditions of one or more airport elements. It can also be measured in more quantitative terms such as waiting time, crowding, processing time, etc.

In landside planning, the Level of Service (LOS) is a crucial target to establish since it is one of the key factors for airport cost and its publicity. A high LOS may cause the available capacity insufficient for its demands, and a low LOS may induce into a loss of passengers and business opportunities. In order to evade these potential threats, a good capacity estimation and selection of LOS is critical to landside planning. The IATA provides some methods of LOS planning where airport managers select a LOS on the basis of different tables, which provide description of LOS classifications and different standards associated with each LOS (IATA Level of Service,2017).

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Figure 3.2: LOS Guidelines (extracted from (IATA Level of Service,2017))

Even though the IATA method is used by many airports, it just provides gross estimates of capacity, which are mostly static and deterministic. Over the years, several other tools have been developed to better aid in LOS analysis.

One of the most recent models is the Simple Landside Aggregate Model (SLAM) fromBrunetta et al.(1999), which consists in a simple set of mathematical formulas used to estimate capacities of each facility and the LOS associated with it, quantified in terms of space available per occupant and waiting time for being processed.

3.1.2 Airside Capacities

Airside capacity is a more complex system simply because there exist many factors which can affect the capacity value. Usually, the airside system is designed to accommodate the volume and type of aircraft that populate the airport. It’s a system with a lot of facilities, being the more crucial ones:

• Runway System: where aircraft arrive and depart. It is considered the most important facility of an airport, since the amount of runways, the layout and length will determine the types of aircraft that can use the airport, as well as the number of aircraft movements in the airport.

• Apron System: where aircraft are parked, loaded, unloaded, refueled or boarded. The apron capacity is only occasionally a constraining factor in regards to airside capacity.

• Taxiway System: it is the system that connects runways with aprons, terminals and other facilities. Typically constructed with the purpose of high speed or rapid-exit to allow aircraft to leave the runway quickly.

As stated above, there are many factors that affect airside capacity, and more in particular, the runway capacity since it is the most important facility of the airport. A detailed document about airport systems byDe Neufville and Odoni (2013) contains information about the most relevant factors which are described below.

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3.1 Airport Capacities 19

1. Layout and number of runways: The runways of an airport are responsible for most of the capacity of an airport due to how they are a crucial part of its system. The greater the amount of existing runways, the higher the capacity and flexibility of the airport since it allows for numerous movements in parallel.

The layout also affects the flexibility in the runway system, since there are three possible layouts, the close parallel runways, the independent runways and the medium-spaced run-ways. The close parallel runways make it so that arrivals and departures cannot be made at the same time on each runway. The independent runways allow for arrivals and departures at the same time in each runway. When the runways are medium-spaced, arrivals are not permitted to be made at the same time, however, independent departures or independent arrivals and departures are completely allowed.

Furthermore, layouts with different directions ensure even more flexibility, since they allow coverage for different wind directions. Length is also an important factor since it defines the kind of aircraft that can use the airport.

2. Aircraft Types and Performance: The capacity of a runway can be greatly influenced by the different types of aircraft using it. Depending on the characteristics of the aircraft, such as size, aerodynamics, propulsion and braking performance, the capacity will vary accordingly, i.e. larger aircraft will require a larger amount of time for landing and taking off and longer runways for the movement.

Pilot training and experience is also an important factor, since inexperience pilots will cause operation slowdowns.

3. Air Traffic Management: As referred inDe Neufville and Odoni (2013), there is a system defined as Air Traffic Management system (ATM). This system is supported by personnel and software that allows airports to adapt efficiently their capacity regarding several factors variations. To guarantee a high quality ATM system, it must be composed by well-trained air traffic controllers and supported by good decision support systems.

The ATM system usually has to face issues such as, the variety between aircraft movement combinations, i.e. independent arrivals, independent departures or a mix of arrivals and departures, the type of aircraft, weather conditions etc. This issues are what the ATM system must face to ensure a proper optimal decision towards capacity.

4. Weather: The weather is usually an important factor affecting airport capacity and one of the most difficult to calculate due to its unpredictability. Snow, ice, heavy fogs, rain and heavy winds can reduce the ability of an airport to accommodate aircraft or even causing a full shutdown, mostly since the weather factor affects in a bigger way the runway system. 5. Environmental Considerations: When referring to environmental considerations the most

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areas must operate with capacity limitations in periods where high noise isn’t acceptable, i.e. mostly during night time.

6. Apron and Taxiway: The apron and the taxiway system aren’t usually the most restrictive elements of the airside system. It is still crucial that they are well designed and managed to prevent issues such as short taxiway segments that may cross active runways.

There are already mathematical models for runways, taxiways and aprons imposing restric-tions such as aircraft types, number of aircraft, number of people flow etc., to try and optimize as best as possible the capacity of each element.

3.2 Airport Congestion

Airport congestion in this chapter will be mostly focused on congestion caused by flight delays since this thesis discusses slots which focus in schedules.

Congestion occurs whenever demand exceed capacity. In the case of airports, congestion usually occurs due to imbalance between scheduling and the capacity of the airport, which causes the occurrence of flight delays.

Flight delays are currently one of the major threats that airports face. As mentioned in chap-ter 1, the air traffic market has been growing a lot in the last few years causing an increased difficulty to match capacity to the demands. This increased difficulty to match demands caused flight delays to become even more prominent, causing loss of level of service and economic costs to airports (Wandeler,2008).

Due to the flight delay issues, the importance of finding a solution to mitigate the problem of airport congestion has been a priority over the years. Flight delays may occur because of several reasons.

• Firstly, flight delays will occur whenever flight demands exceed the maximum throughput capacity. This type of delays is a consequence of excessive schedule of flights that eventually will overload the schedules. These are called overload delays.

• Secondly, flight delays may also occur when expected flight demand is lower that airport ca-pacity. This type of delays is caused when the times at which flights take place are different than the times the airport need to process these flights. These are called stochastic delays. The number of flights that the airports can process depend on the factors presented in sec-tion3.1. These factors are what decide the variations of airport service over the day.

3.2.1 Congestion Mitigation

To mitigate congestion, solutions must be brought up. This solutions may be divided into three different categories. Firstly, there can be a long term solution through the expansion of airports. Secondly, a short and medium term solution could be the mitigation through demand management

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3.2 Airport Congestion 21

measures. And finally, at the day of operations, air traffic flow management procedures may aid in minimizing the impacts of congestion.

1. Airport Expansion:

As it’s been stated previously, airport congestion has been increasing over the years due to increase in demands. It is important to mitigate congestion and for that reason, long term solutions must arise to accommodate the expected flight demand.

Airports might begin thinking in expanding their available capacity by building new land-side and airland-side facilities such as runways, aprons or terminals. Each capacity bottleneck will dictate which system the airport should focus in expanding. Even though these seem direct solutions, limitations are always present. The lack of empty space close to the air-ports to allow the expansions may prove difficult, noise restrictions and huge costs also are limitations to airport expansions.

When expansion proves to be a difficult task, building a new airport or even replace the existing ones may be the only alternative. However, the construction of a new airport always requires a substantial amount of capital which is not always available.

2. Demand Management:

Even though airport expansion is considered the most obvious way to increase airport ca-pacity, it is a solution that requires a long time and a substantial amount of resources before becoming effective. In order to find another solution to short and medium terms, demand management measures seem to be the alternative solution available to try and mitigate de-lays.

Demand management refers to a set of administrative or economic measures and regulations that aim to constrain flight demand at busy airports. This can be made in several ways, such as, limiting demands for access at congested airports by declaring limit capacity that prevents it, modifying the temporal distribution of demands to bring it closer to available capacity by performing schedule adjustments.

Usually airport demand management can be approached in different ways. It can be made utilizing a administrative approach typically consisting on voluntary schedule adjustments, performed by airport representatives or other entities, with the objective of reducing the number of flights scheduled at peak hours and distributing them evenly over the day. The IATA slot allocation process has been the most used administrative demand manage-ment mechanism as stated in chapter2. It is a process that allocates slots throughout sched-ules having into account the declared capacities by the airport. Despite having several ad-vantages there are some inconveniences mainly to new entrants. Empty slots tend to be only available at unattractive times, airlines are reluctant to give up their historic slots and

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The economic approach involve market mechanisms in order to influence the choices of airlines concerning airport access. It consists in a system of fees based on congestion pric-ing. This makes the pricing scheme vary during the day, imposing higher fees during peak demand periods, and lower fees during off-peak periods. Even thought this economic ap-proach might seem reasonable, smaller airlines may find it discriminatory since they have no way of paying high fees for the peak hours slots.

3. Air Traffic Flow Management:

Congestion may occur during the day of operations due to unexpected situations such as weather issues, aircraft performance problems and other disruptions. These are highly un-predictable situations that can be resolved by utilizing long, medium or short term methods. In order to manage these situations, air traffic flow management procedures must be used to minimize congestion. The main objective of Air Traffic Flow Management is to guaran-tee that aircraft can flow through airspace efficiently, preventing the occurrence of expected overloads that might affect airspace safety and minimizing the economic impacts imposed by flight delays. This can be accomplished by adjusting the flow of aircraft dynamically in order that demand matches available capacity.

For the purpose of this thesis, the focus will be on Demand Management since it is the method which involves slots and can be studied effectively with an outside perspective without requir-ing confidential information. In section 3.3 some already existing optimization models will be described to show how schedule management can be made to prevent airport congestion.

3.3 Existing Optimization Models

Due to airport congestion there is a necessity to support slot coordinators in their process of slot allocating to better accommodate airlines preferences at coordinated airports. Two optimization models will be discussed to reveal how they can aid slot coordinators and how there still is room for improvement.

The model byZografos et al. (2012) is a model focused on the IATA rules, optimizing the scheduled adjustments for an entire season and taking into account the definition of series of slots. However, this model does not take into account some important operational and regulatory constrains faced by airports.

The model byPyrgiotis et al.(2013) is a model that examines the implication of schedule limits such as declared capacities, however, it does not take into account the IATA rules and considers only a single day of operation instead of a full season, which is required by the definition of series of slots.

3.3.1 The Zografos Model

This model is a single-airport optimization model, which minimizes the total displacement be-tween the airlines requested and allocated slot times. It takes into account the slot priorities set by

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3.3 Existing Optimization Models 23

IATA and solve the allocation problem for the entire season, fully complying with the definition of series of slots. The model was applied to several Greek airports and compared its outcomes with the ones produced by slot coordinators. It was demonstrated that there was a large room for improvement in efficiency of the current allocation process.

The model has an objective function that minimizes the total absolute difference between the requested and allocated slot time. Constraints ensure that no flight movement is eliminated, total number of movements cannot exceed the slot limits defined and force connection time to be larger than minimum turnaround time.

The formulation for the model is presented in Figure3.3:

Figure 3.3: Zografos model (extracted from (Nuno Antunes Ribeiro,2016))

The model uses a series of sets and parameters (Figure 3.4) that indicate several indicators that must be used for the calculations, such as set of time intervals per day, set of days, set of series of flights, cost of allocating flights, etc., with the objective of minimizing the displacement of schedules to avoid a large amount of delays. It functions well given small samples, but when it starts dealing with a larger amount of information, the result may lead to a large displacement of schedules, since a smaller sample can result in feasible solutions but larger amounts of requests

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Figure 3.4: Zografos model Sets and Parameters (extracted from (Nuno Antunes Ribeiro,2016))

3.3.2 The Pyrgiotis Model

This model is an airport network optimization model which reschedules airline flight requests according to scheduling limits specified by airports. In order to achieve that objective, a new schedule is generated, minimizing the maximum schedule displacement experienced by any single flight and minimizing also the aggregate schedule displacement across all flights. There is no elimination of flights and the model respects all aircraft itineraries and passenger connections.

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Unlike the Zografos model, this model optimizes flight schedules for any single day of opera-tions, however, it is not in accordance with the rules set by IATA, and in particular, the concept of series of slots.

The formulation of the model is presented in Figure3.5:

Figure 3.5: Pyrgiotis model (extracted from (Nuno Antunes Ribeiro,2016))

The objective function of the model consists of two parts. Firstly it minimizes the maximal displacement that any given flight will sustain. Secondly, among all schedules that can be obtain from the first part, it selects the one that minimizes total displacement. The constrains ensure that

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flight is eliminated, that the total of flights per time cannot exceed the arrival, departure and total slot limits, and that connection time between flights is the same as originally requested.

The sets and parameters (Figure3.6) used by this model consist in set of flights, set of periods, set of flight pairs, maximum departure and arrival slots, total number of slots, etc.

Figure 3.6: Pyrgiotis model Sets and Parameters (extracted from (Nuno Antunes Ribeiro,2016)) Both models presented are effective in aiding slot coordinators in different situations, although they can falter in situations with larger examples, or they are not fully compliable with the IATA rules, and also still be unfair to new entrants.

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To that end, Chapter4will talk about how a decision support system can aid slot coordinators in re-scheduling to minimize congestion and delays taking into account slot definition, IATA rules and the airport declared capacities.

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Chapter 4

Solution Approach

As stated before, the continuous growth of airline traffic as been a problem for airports since it brings up issues like airport congestion, which leads to schedules delays. This is a negative side that has been tried to be mitigated using different approaches already referred in Chapter3.

One of the solutions stated that a demand management approach is one that can, in short and medium terms, implement measures that minimize the airport congestion and therefor mitigate delays.

The economic approach for this thesis is not considered since it requires higher administrative supervision. In that case, the administrative approach through slot coordination is the method applied. The objective of slot coordination is to voluntarily adjust schedules with the objective of reducing the number of flights at peak hours and distribute them more evenly over the day.

The most used administrative mechanism is the IATA slot allocation process, which allocates slots throughout schedules taking into account the declared capacities by the airport. The IATA also presents a set of rules that establish priorities considering the different properties of slot requests. This method brings several advantages but also disadvantages, mostly to new entrants, since empty slots tend to be only available at times which seem unattractive.

Nevertheless, considering it brings a system that manages to properly allocate most schedules it is still the best method to use at congested airports, however changes can be applied to try and upgrade the process or give a better view to slot coordinators so that a better admissible solution can be achieved.

4.1 Decision Support System

In order to try and upgrade the IATA slot allocation process, the idea of having a decision support system (DSS) was brought up to aid slot coordinators to better manage the process.

A decision support system is an information system that allows the users to reach a decision through a series of inputs and information displayed to them. This decision system can be fully computerized, human-based or a combination of both. Usually a DSS is used as a tool in important decision-making environments as it facilitates organizational processes.

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30 Solution Approach

In a DSS architecture, there are to be taken into account three fundamental components (ac-cording to Sprague and Carlson(1982) andHolsapple and B. Whinston(2018)):

1. The database: where the information is stored for use in the DSS. 2. The Model: the decision context and user criteria.

3. The User-interface: where the user can see the results and formulate a decision.

After having these components, the DSS must follow a structured approach in order to be the most efficient. The approach can be divided in four phases:

1. Intelligence: Searching for conditions that will lead to decisions. 2. Design: Developing and reviewing possible alternatives for solutions. 3. Choice: Selecting a course of action.

4. Implementation: Adopting the selected choice.

Finally, after having the architecture structured and the approach designed, the DSS has four components to take into account for its implementation:

1. Inputs: the data needed to be analyzed.

2. User knowledge: the input data requiring manual analysis. 3. Outputs: the transformed data that leads to decision generation. 4. Decisions: the results generated by the DSS.

Having in mind all of these definitions, a decision support system was made for this thesis in order to aid slot coordinators in their slot allocation process.

4.2 Applied Method

Firstly, to apply the DSS to this problem, it was needed to analyze the available data and how the information is given to the user to understand how a DSS structure could be implemented. The DSS would need to have as information, the declared capacities of the airport as well as the information that a slot requests in order to have in the database.

In order to understand how the inputs of the DSS would be, a series of websites were visited to understand the format and the information that was given to slot coordinators. According to the ANA Coordenação de Slots(2018), slot requests must follow a precise format, with all the information of the requirement such as operation time, frequency of operation, time of day, etc.

The request, in order to be valid must follow the following format: HEADER

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4.2 Applied Method 31

SCR = name of message / = creator reference

W10 (IATA SEASON W10 – Winter 2010 / S10 – Summer 2010) 10JAN = date of message

LIS = airport of clearence DATA LINES

Z XXXXX XXXXX AAAAAAAAAA 1234567 BBB CCC DDD EEEE FFFF GGG HH FOOTER

GI Brgds

For the DSS, the only segment that it will analyze will be the Data Lines segment, since that is where the information for the schedule allocation is located. The information present in the request is as follows (information withdrawn fromANA Coordenação de Slots(2018)):

1. Z = Action Code N - for new flights

C - for flights I want to change (data to be changed) always followed by a new line starting with R

R – new data line

D - for flights to be cancelled A – acceptance of an offer

P – pending of an offer (keeping the initial required times in waitlist for future improvement) Z – declining offer

2. XXXXX = Flight Number

For operators having flight numbers the first digits represents the IATA or ICAO code fol-lowed by 3 or 4, numeric as the fight number.

3. AAAAAAAAAA = Period of Operation

Date and month, for example a single date, 03MAY or for a period, 03MAY28JUN. 4. 1234567 = Day(s) of Operation

1 to 7 is Monday to Sunday, for example a Monday operation, 1000000, or a weekend operation, 0000067.

5. BBB = Number of Seats

Number of seats in the aircraft for example 048. For cargo or positioning flights use 000. 6. CCC = Aircraft Type

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7. DDD = Airport of Origin

IATA airport code 3 digits. When there is no IATA code please use code XXX and men-tioned in SI the ICAO code 4 digits, for example LPCS.

8. EEEE/FFFF = Time of Arrival / Time of Departure Arrival / Departure time scheduled is always in UTC. For LIS, OPO, FNC and FAO

UTC: Winter = local time / Summer = local time –1 For PDL

UTC: Winter = local time - 1 / Summer = local time 9. GGG = Airport of Destination

IATA airport code 3 digits. When there is no IATA code please use code XXX and men-tioned in SI the ICAO code 4 digits, for example LPCS.

10. H = Type of Service Type of service: J = Schedule passenger C = Charter passenger H = Charter cargo F = Schedule cargo P = Positioning K = Training W = Military E = Special Government I = State/Diplomatic/Air..ambulance T = Technical Test

11. SI/GI = Supplementary/General Information

It is mandatory that any free text following the data line(s) always starts with ‘SI’ or ‘GI’. In the DSS created in this thesis the eleventh point isn’t considered since it is part of the footer and the data lines is the most important part of the slot request with all the information needed.

Also, as part of the information needed, the declared capacities play a big role in the decision process, since it imposes restrictions that must be followed in order to not surpass the airport capacities.

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4.2 Applied Method 33

In Figure3.1an example taken fromANA Coordenação de Slots(2018) shows how the Porto airport declared capacity is shown to the slot coordinator. However in other airports we can see different forms of declared capacities, even though they possess a similar form.

Figure4.1and Figure4.2show other examples of how declared capacities can be presented, depending on the rules imposed by the airport.

Figure 4.1: Madeira airport declared capacities (extracted from (ANA Coordenação de Slots,

2018))

Figure 4.2: Lisboa airport declared capacities (extracted from (ANA Coordenação de Slots,2018)) Since the thesis focuses on a simpler example for the DSS, and since there wasn’t access to more confidential information such as official slot requests, a fictional airport was created, based on the declared capacities presented by the Porto airport shown in Figure3.1.

Table4.1shows the declared capacities of the fictional airport created for this thesis. It changes the passengers flow arrival or departure to blocks of 15 minutes for demonstrative purposes since

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Table 4.1: Fictional Airport Declared Capacities Runway

Total movements per 60’ 5 Arrival/Departure per 60’ 4 Total movements per 15’ 3 Arrival/Departure per 15’ 2

Apron

Capacity 7

Terminal Pax Flow Arrival or Departure

per 15’ 500

After creating a fictional airport to use as a case study for the thesis, slot requests were also created to have information as inputs in the database for the DSS. The slots follow the format as shown previously to be as close as possible to a real life example. The values were created ran-domly, but with focus on a specific time of day to create congestion in schedules. The information such as flight number, airport of origin, airport of destination and aircraft type were not important for this DSS so the values there may not follow the IATA guidelines. The requests created were as follows:

1. N BD615 05DEZ05DEZ 0100000 150 XXX OPO0900 0945LIS J 2. N ST937 27OCT27MAR 1111100 300 XXX OPO0900 0945LIS J 3. N BD615 27OCT27MAR 1010101 100 XXX OPO0900 0945LIS J 4. N BD615 27OCT27MAR 1100000 075 XXX OPO0815 0900LIS J 5. N BD615 27OCT27MAR 0000100 350 XXX OPO0900 0945LIS J 6. N BD615 01DEZ12DEZ 1100000 125 XXX OPO0900 0945LIS J 7. N BD615 01DEZ12DEZ 1000010 000 XXX OPO0900 0945LIS K 8. N BD615 05DEZ05DEZ 0100000 000 XXX OPO0700 0945LIS W 9. N BD615 01NOV31DEZ 1001000 000 XXX OPO0800 0930LIS F

As can be seen in the requests created, there was a focus in the bloc of 9h to 10h in order to create a scenario where various requests were overlapping to create congestion and see if the DSS could be helpful based on the information it had.

In earlier stages of the thesis, the case study created was solved by hand to see if it was possible to come to a conclusion with the information presented. Following a first-come-first-served basis, the order presented above would cause a multitude of unnecessary delays. The first request for example, is a request for one day only, so when the capacity of that hour slot would reach its limit, a request that had a larger operational time would have to suffer a delay to accommodate a