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  • Linkping Studies in Science and Technology Licentiate Thesis No. 1388

    Airport Logistics Modeling and Optimizing the Turn-Around Process

    Anna Norin

    Department of Science and Technology Linkping University, SE-601 74 Norrkping, Sweden

    Norrkping 2008

    LIU-TEK-LIC-2008:46

  • Airport Logistics Modeling and Optimizing the Turn-Around Process Copyright Anna Norin

    anna.norin@itn.liu.sehttp://www.itn.liu.seDepartment of Science and Technology ISBN 978-91-7393-744-3 ISSN 0280-7971 LIU-TEK-LIC-2008:46

    Printed by LiU-Tryck, Linkping, Sweden, 2008

  • Abstract

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    ABSTRACT

    The focus of this licentiate thesis in the area known as infra informatics, is air transportation and especially the logistics at an airport. The concept of airport logistics is investigated based on the following definition: Airport logistics is the planning and control of all resources and information that create a value for the customers utilizing the airport. As a part of the investigation, indicators for airport performance are considered.

    One of the most complex airport processes is the turn-around process. The turn-around is the collective name for all those activities that affect an aircraft while it is on the ground. In the turn-around process almost all of the actors operating at the airport are involved and the process is connected to other activities which take place on airside, in the terminal as well as in the control tower. This makes the turn-around process an excellent focal point for studying airport logistics.

    A detailed conceptual model of the turn-around process is developed and a simplified version of this is implemented in a computerized simulation program. The aim of the simulation is to enable the assessment of various logistical operations involved in turn-around, and their impact on airport performance. The flow of support vehicles serving the aircraft with fuel, food, water etc during the turn-around is received particular attention. The output from the model can be used as indicators for the airport performance.

    One of the most interesting support flows to study is the flow of de-icing trucks. De-icing is performed to remove ice and snow from the aircraft body and to prevent the build up of new ice. There is a limited time span prior the take off, within which de-icing has to be performed. This makes the time of service critical. An optimization approach is developed to plan a schedule for the de-icing trucks. Scheduling the flow of de-icing trucks can be seen as a heterogeneous vehicle routing problem with time windows. The objective of the optimization is total airport performance and a heuristic method is used to solve the problem.

    The optimized schedule for the de-icing trucks is used as input in the simulation model. The schedule optimized for the entire airport is compared to a schedule based on a simpler scheduling rule as well as a schedule optimized for the de-icing company. By running the model with the different routings, it is found that the schedule optimized for the entire airport gives the best results according to the indicators specified for measuring airport performance.

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  • Acknowledgement

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    ACKNOWLEDGEMENT

    First of all, I would like to thank my supervisors at ITN, Peter Vrbrand, Tobias Andersson Granberg and Di Yuan for always being inspiring and finding new ways of thinking. I am also thankful to all my other colleagues at ITN for making this such a stimulating environment to work in. My roommate Joakim deserves special thanks for many pleasant and fruitful discussions and for never wearying of my stupid questions.

    I would also like to express my deepest gratitude to the LFV Group, both the ANS and LFV Teknik departments, for the financial funding of this project. Especially thanks to my supervisors at LFV; Niclas Gustavsson and Johann Rolln, for turning this work into the right direction. All the people at Stockholm Arlanda Airport, both from LFV, Nordic Aero, SAS and others, who have taken their time to support me with information and statistical data also deserves a great acknowledgement. I would like to take this opportunity to show my appreciation to all my colleagues at LFV Teknik, where I still spend part of my working time, for keeping me updated on the subject of airports and ensuring no day at the office without a laugh.

    Finally, I want to thank all my family and friends. Special thanks to Johanna, for convincing me to start this study; Magnus, for your helpful comments on the work; and all other for making me have a good time when I am with you. Last and most of all, I would like to thank Tobias for all your love and for always supporting me and believing in me (especially when I do not) and our unborn child who sometimes kicks me just as a remainder that this thesis is not the most important thing in the world

    Norrkping, November 2008

    Anna Norin

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  • List of Acronyms and Abbreviations

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    LIST OF ACRONYMS AND ABBREVIATIONS ACC Area Control Center AIP Aeronautical Information Package AL Airport Logistics ANS Air Navigation Services APOC Airport Operations Centre ARCPort Airport specific simulation software ARENA General simulation software ASI Airport Simulation International ATC Air Traffic Control ATFM Air Traffic Flow Management ATM Air Traffic Management ATS Air Transportation System BIP Binary Integer Programming CAST Airport specific simulation software CDM Collaborative Decision Making DLR Deutsches Zentrum fr Luft- und Raumfahrt (German Aerospace Center) DSS Decision Support System EEC Eurocontrol Experimental Centre EC European Commission FMS Flight Management System GPU Ground Power Unit GQM Goal Question Metric GRASP Greedy Randomized Adaptive Search Procedure GWAC Greedy with availability check GWOAC Greedy without availability check HVRP Heterogeneous fleet Vehicle Routing Problem IATA International Air Transport Association ICAO International Civil Aviation Organization IP Integer Programming KPA Key Performance Areas KPI Key Performance Indicators LFV Swedish Civil Aviation Administration MACAD Mantea Airfield Capacity And Delay Model MIP Mixed Integer Programming NP Nondeterministic Polynomial time OPAL Optimization Platform for Airports Including Landside OR Operations Research Pax Passengers RCL Restricted Candidate List RET Rapid Exit Taxiway

  • List of Acronyms and Abbreviations

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    RTF Radio Telephone RWY Runway SA Stockholm Arlanda Airport SAS Scandinavian Airline System SFS Stockholm Fueling Services AB SGS SAS Ground Service SIMMOD Airport and Airspace Simulation Model SLAM Simple Landside Aggregate Model SPADE Supporting Platform for Airport Decision-making and Efficiency

    Analysis STA Scheduled Time of Arrival STD Scheduled Time of Departure STS SAS Technical Services AB TAAM Total Airspace and Airport Modeller TAM Total Airport Management THENA THEmatic Network on Airport Activities TMC Terminal Control Center TSP Traveling Salesman Problem TWR The control tower VBA Visual Basic for Applications VRP Vehicle Routing Problem VRPTW Vehicle Routing Problem with Time Windows WX Weather conditions

  • Table of Contents

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    TABLE OF CONTENTS

    ABSTRACT I ACKNOWLEDGEMENT III LIST OF ACRONYMS AND ABBREVIATIONS V TABLE OF CONTENTS VII LIST OF FIGURES IX LIST OF TABLES X 1 INTRODUCTION ......................................................................................................1

    1.1 SCOPE ..................................................................................................................2 1.2 DELIMITATIONS ...................................................................................................3 1.3 METHODOLOGY ...................................................................................................3

    1.3.1 Simulation.......................................................................................................3 1.3.2 Optimization ...................................................................................................5 1.3.3 Integration of optimization and simulation ....................................................6

    1.4 CONTRIBUTIONS ..................................................................................................8 1.5 OUTLINE ..............................................................................................................9

    2 OPERATIONS RESEARCH IN AIR TRANSPORTATION...............................11 2.1 THREE MAIN ACTORS IN AIR TRANSPORTATION.................................................11 2.2 RESOURCE MANAGEMENT FOR AIRLINES ...........................................................12 2.3 RE