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Mitigating Airport Congestion: Market Mechanisms and Airline Response Models by Pavithra Harsha B.Tech., Mechanical Engineering Indian Institute of Technology, Madras, India (2003) Submitted to the Sloan School of Management in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Operations Research at the MASSACHUSETTS INSTITUTE OF TECHNOLOGY February 2009 c Massachusetts Institute of Technology 2009. All rights reserved. Author.............................................................. Sloan School of Management August 21, 2008 Certified by. Cynthia Barnhart Professor of Civil and Environmental Engineering School of Engineering Associate Dean for Academic Affairs Co-Director, Operations Research Center Thesis Supervisor Certified by. David C. Parkes Gordan McKay Professor of Computer Science, Harvard University Thesis Supervisor Accepted by . Dimitris Bertsimas Boeing Professor of Operations Research Co-Director, Operations Research Center 2 Mitigating Airport Congestion: Market Mechanisms and Airline Response Models by Pavithra Harsha Submitted to the Sloan School of Management on August 21, 2008, in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Operations Research Abstract Efficient allocation of scarce resources in networks is an important problem worldwide. In this thesis, we focus on resource allocation problems in a network of congested airports. The increasing demand for access to the world's major commercial airports combined with the limited operational capacity at many of these airports have led to growing air traffic congestion resulting in several billion dollars of delay cost every year. In this thesis, we study two demand-management techniques { strategic and operational approaches { to mitigate airport congestion. As a strategic initiative, auctions have been proposed to allocate runway slot capacity. We focus on two elements in the design of such slot auctions { airline valuations and activity rules. An aspect of airport slot market environments, which we argue must be considered in auction design, is the fact that the participating airlines are budget-constrained. The problem of finding the best bundle of slots on which to bid in an iterative • combinatorial auction, also called the preference elicitation problem, is a par- ticularly hard problem, even more in the case of airlines in a slot auction. We propose a valuation model, called the Aggregated Integrated Airline Scheduling and Fleet Assignment Model, to help airlines understand the true value of the different bundles of slots in the auction. This model is efficient and was found to be robust to data uncertainty in our experimental simulations. Activity rules are checks made by the auctioneer at the end of every round • to suppress strategic behavior by bidders and to promote consistent, continual preference elicitation. These rules find applications in several real world sce- narios including slot auctions. We show that the commonly used activity rules are not applicable for slot auctions as they prevent straightforward behavior by budget-constrained bidders. We propose the notion of a strong activity rule which characterizes straightforward bidding strategies. We then show how a strong activity rule in the context of budget-constrained bidders (and quasi- 3 linear bidders) can be expressed as a linear feasibility problem. This work on activity rules also applies to more general iterative combinatorial auctions. We also study operational (real-time) demand-management initiatives that are used when there are sudden drops in capacity at airports due to various uncertain- ties, such as bad-weather. We propose a system design that integrates the capacity allocation, airline recovery and inter-airline slot exchange procedures, and suggest metrics to evaluate the different approaches to fair allocations. Thesis Supervisor: Cynthia Barnhart Title: Professor of Civil and Environmental Engineering School of Engineering Associate Dean for Academic Affairs Co-Director, Operations Research Center Thesis Supervisor: David C. Parkes Title: Gordan McKay Professor of Computer Science, Harvard University 4 Credits This thesis is a result of joint work with Cynthia Barnhart and David Parkes. I thank them for this collaboration. I thank David's group at Harvard { Haoqi Zhang, my co-author on the Activity Rules paper [HBPZ08], for all our discussions on the slot auctions and his help with the JAVA programming, Rui Dong for our initial work on integrating the valuation model with the clock auction, Sebastien Lahaie for the iBundle codes and Ben Lubin for discussions on slot exchanges. I thank Mallory Soldner, Doug Fearing and Constantine Caramanis for our discussions and collaboration on the real-time slot allocation work. I would also like to thank Bob Day and Peter Cramton for providing me with feedback on my work on activity rules. I especially would like to thank Hamsa Balakrishnan who made several useful suggestions to me in my research I thank Bob Hoffman and Rohit Viswanathan from Metron Aviation for providing data about GDPs. I also thank FAA and NSF-EFRI for providing us with partial funding for this work and NEXTOR group for the opportunity to participate in their simulation games. My thesis committee consisted of Cynthia Barnhart, David Parkes and Hamsa Balakrishnan. 5 6 Acknowledgments This thesis would not have been possible but for the valuable advice and guidance of my advisors, Cynthia Barnhart and David Parkes. I am deeply indebted to both for the collaboration that opened doors to two fascinating areas, airlines and auctions, and their intermix. I sincerely thank Cindy for her unwavering support, encouragement and invalu- able guidance. She gave me complete freedom in choosing research directions and en- couraged and supported all collaborations. I have greatly benefited from her unique research style; an appropriate balance between theory and practice, and her insights on crisp modeling of real-world problems. Above all, her humane nature, patience, energy to keep going for hours, work-life balance and her style have truly amazed me. I started working with David a year into my PhD. His passion towards mechanism design and its applications has never ceased to motivate and inspire me. His prompt and detailed response to my emails, led us many times to conduct in-depth research conversations over emails, which I really enjoyed. His constant support and invaluable guidance in research and in finding internships and full-time positions have greatly helped me and for that, I am truly grateful. I have learnt a lot from both Cindy and David and it has been a pleasure working with both. Special thanks to Hamsa, my other thesis committee member, for spending hours discussing research and providing me with valuable feedback that improved the quality of my thesis. I thank Haoqi Zhang, Ben Lubin, Lavanya Marla, Hai Jiang, Mike Hanowsky, Bob Hoffman, Rui Dong, Sebastien Lahaie, Adam Juda, Mallory Soldner, Doug Fearing, Constantine Caramanis, Mike Ball, Bob Day, Peter Cramton for several valuable discussions, input and feedback during my research. I have greatly benefited from my summer internships at HP Labs and Emptoris. Tad Hogg and Kay-Yut Chen at HP were excellent mentors and enthralled me into quantum games. With Olga Raskina's mentoring at Emptoris, I got a glimpse into applications of auctions in the real world. 7 I thank my undergraduate professor G. Srinivasan, a fantastic teacher, for intro- ducing me to the world of OR. He was one of the main reasons I pursued my doctoral studies in OR. I thank Maria Marangiello for arranging my regular meetings with Cindy, making me comfortable and enquiring about my well-being. Thanks to Laura, Paulette and Andrew, who run the ORC extremely efficiently and are always on the look out for making the life of students at ORC very comfortable. My friends at the ORC, Pamela, Pranava, Lava, Rags, Hamed, Dan, Dave, Nelson, Theo, Carine, Amr, Shobhit, Kwong-Meng, and others made my life in the ORC an experience that I will cherish with memorable conversations and enjoyable times. I thank my other MIT friends, Pranava, Vinutha, Lava, Rags, Anu, Sreeja, Surana, Sonal, Vijay, Amit, Kripa, Shashi and others in the India Reading group for having created a home away from home. A very special thanks to Lava and Pranava who have been very caring, encouraging and greatly helped me get over my occasional blues. I sincerely thank Vikram and Ramesh for all the good times we have spent together and their ideals, goals and dreams that have inspired me, to whom I am forever grateful. I thank Aai and Baba and everyone in my extended family who have shown their constant affection and support. Finally, no words can suffice my eternal thanks and love for Amma, Appa, Anna and Ajay for believing in me and who keep me going. Anna, my strength, my pillar and my limit, I dedicate this to you. 8 Contents 1 Introduction 17 1.1 Procedures to Mitigate Congestion................... 19 1.1.1 Demand-Management Policies.................. 21 1.2 Thesis Contributions and Outline.................... 22 1.2.1 Chapter 2: Strategic Approaches to Mitigate Airport Congestion 22 1.2.2 Chapter 3: Airline Response to Airport Slot Auctions and Chapter 4: Activity Rules for Iterative Combinatorial Auctions 24 1.2.3 Chapter 5: Real-Time Approaches to Mitigate Airport Conges- tion................................ 26 2 Strategic Approaches to Mitigate Airport Congestion 29 2.1 Airport Slot Allocation.........................

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