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Modelling and Solving the Single-Airport Slot Allocation Problem.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modelling and Solving the Single-Airport Slot Allocation Problem./
作者:	Katsigiannis, Fotios A.
面頁冊數:	1 online resource (382 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-01, Section: B.
Contained By:	Dissertations Abstracts International84-01B.
標題:	Schedules. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=29180713click for full text (PQDT)
ISBN:	9798835551903

Modelling and Solving the Single-Airport Slot Allocation Problem.
Katsigiannis, Fotios A.

Modelling and Solving the Single-Airport Slot Allocation Problem. - 1 online resource (382 pages)

Source: Dissertations Abstracts International, Volume: 84-01, Section: B.

Thesis (Ph.D.)--Lancaster University (United Kingdom), 2022.

Includes bibliographical references

Currently, there are about 200 overly congested airports where airport capacity does not suffice to accommodate airline demand. These airports play a critical role in the global air transport system since they concern 40% of global passenger demand and act as a bottleneck for the entire air transport system. This imbalance between airport capacity and airline demand leads to excessive delays, as well as multi-billion economic, and huge environmental and societal costs. Concurrently, the implementation of airport capacity expansion projects requires time, space and is subject to significant resistance from local communities. As a short to medium-term response, Airport Slot Allocation (ASA) has been used as the main demand management mechanism.The main goal of this thesis is to improve ASA decision-making through the proposition of models and algorithms that provide enhanced ASA decision support. In doing so, this thesis is organised into three distinct chapters that shed light on the following questions (I-V), which remain untapped by the existing literature. In parentheses, we identify the chapters of this thesis that relate to each research question.I. How to improve the modelling of airline demand flexibility and the utility that each airline assigns to each available airport slot? (Chapters 2 and 4)II. How can one model the dynamic and endogenous adaptation of the airport's landside and airside infrastructure to the characteristics of airline demand? (Chapter 2)III. How to consider operational delays in strategic ASA decision-making? (Chapter 3)IV. How to involve the pertinent stakeholders into the ASA decision-making process to select a commonly agreed schedule; and how can one reduce the inherent decision-complexity without compromising the quality and diversity of the schedules presented to the decision-makers? (Chapter 3)V. Given that the ASA process involves airlines (submitting requests for slots) and coordinators (assigning slots to requests based on a set of rules and priorities), how can one jointly consider the interactions between these two sides to improve ASA decision-making? (Chapter 4)With regards to research questions (I) and (II), the thesis proposes a Mixed Integer Programming (MIP) model that considers airlines' timing flexibility (research question I) and constraints that enable the dynamic and endogenous allocation of the airport's resources (research question II). The proposed modelling variant addresses several additional problem characteristics and policy rules, and considers multiple efficiency objectives, while integrating all constraints that may affect airport slot scheduling decisions, including the asynchronous use of the different airport resources (runway, aprons, passenger terminal) and the endogenous consideration of the capabilities of the airport's infrastructure to adapt to the airline demand's characteristics and the aircraft/flight type associated with each request. The proposed model is integrated into a two-stage solution approach that considers all primary and several secondary policy rules of ASA. New combinatorial results and valid tightening inequalities that facilitate the solution of the problem are proposed and implemented.An extension of the above MIP model that considers the trade-offs among schedule displacement, maximum displacement, and the number of displaced requests, is integrated into a multi-objective solution framework. The proposed framework holistically considers the preferences of all ASA stakeholder groups (research question IV) concerning multiple performance metrics and models the operational delays associated with each airport schedule (research question III).

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798835551903Subjects--Topical Terms:

3564128
Schedules.
Index Terms--Genre/Form:

542853
Electronic books.

Modelling and Solving the Single-Airport Slot Allocation Problem.
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502 $a Thesis (Ph.D.)--Lancaster University (United Kingdom), 2022.
504 $a Includes bibliographical references
520 $a Currently, there are about 200 overly congested airports where airport capacity does not suffice to accommodate airline demand. These airports play a critical role in the global air transport system since they concern 40% of global passenger demand and act as a bottleneck for the entire air transport system. This imbalance between airport capacity and airline demand leads to excessive delays, as well as multi-billion economic, and huge environmental and societal costs. Concurrently, the implementation of airport capacity expansion projects requires time, space and is subject to significant resistance from local communities. As a short to medium-term response, Airport Slot Allocation (ASA) has been used as the main demand management mechanism.The main goal of this thesis is to improve ASA decision-making through the proposition of models and algorithms that provide enhanced ASA decision support. In doing so, this thesis is organised into three distinct chapters that shed light on the following questions (I-V), which remain untapped by the existing literature. In parentheses, we identify the chapters of this thesis that relate to each research question.I. How to improve the modelling of airline demand flexibility and the utility that each airline assigns to each available airport slot? (Chapters 2 and 4)II. How can one model the dynamic and endogenous adaptation of the airport's landside and airside infrastructure to the characteristics of airline demand? (Chapter 2)III. How to consider operational delays in strategic ASA decision-making? (Chapter 3)IV. How to involve the pertinent stakeholders into the ASA decision-making process to select a commonly agreed schedule; and how can one reduce the inherent decision-complexity without compromising the quality and diversity of the schedules presented to the decision-makers? (Chapter 3)V. Given that the ASA process involves airlines (submitting requests for slots) and coordinators (assigning slots to requests based on a set of rules and priorities), how can one jointly consider the interactions between these two sides to improve ASA decision-making? (Chapter 4)With regards to research questions (I) and (II), the thesis proposes a Mixed Integer Programming (MIP) model that considers airlines' timing flexibility (research question I) and constraints that enable the dynamic and endogenous allocation of the airport's resources (research question II). The proposed modelling variant addresses several additional problem characteristics and policy rules, and considers multiple efficiency objectives, while integrating all constraints that may affect airport slot scheduling decisions, including the asynchronous use of the different airport resources (runway, aprons, passenger terminal) and the endogenous consideration of the capabilities of the airport's infrastructure to adapt to the airline demand's characteristics and the aircraft/flight type associated with each request. The proposed model is integrated into a two-stage solution approach that considers all primary and several secondary policy rules of ASA. New combinatorial results and valid tightening inequalities that facilitate the solution of the problem are proposed and implemented.An extension of the above MIP model that considers the trade-offs among schedule displacement, maximum displacement, and the number of displaced requests, is integrated into a multi-objective solution framework. The proposed framework holistically considers the preferences of all ASA stakeholder groups (research question IV) concerning multiple performance metrics and models the operational delays associated with each airport schedule (research question III).
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