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Development of efficient combinatorial auction mechanism for airport slot allocation
Abstract
The current allocation of slots in congested airports is fraught with deficiencies because of the liberalisation of air transportation undertaken all over the world. The existing grandfather rights rule is slowly being replaced with auctions. In the airport slot allocation problem, in order to effectively auction the slots, multiple-item auctions are employed. It is in this aspect that combinatorial auctions are employed, as they are the most efficacious in dealing with complimentarity. Since the existing mechanisms are more inclined towards maximising the auctioneer's profit – with the monetary issue being the only concern – they lead to biased allocations. Therefore, this paper develops a model and proposes a mechanism that could overcome the shortcomings of the existing auctioning procedures by incorporating the concepts of welfare issues with due consideration given to the flight capacity to effectively allot the slots.
... Consequently, many studies recommend an open market for the acquisition of airport slots both in the EU and the US [5]. Mathematical improvements based on optimisation mechanisms [6], [7], and auction markets have already been proposed [8], [9], [10] but none of them studies the problem from a SoSE perspective. This is the motivation to establish a roadmap to tackle this problem from a SoSE perspective and show its benefits. ...
Airport slot allocation is a combinatorial allocation problem (CAP) involving different complex and autonomous systems. Nowadays, the slots are allocated in a two-stage process: primary allocation is performed according to a set of administrative rules and for each airport independently, while secondary allocation is based on trading mechanisms. Several studies have raised inefficiencies in these processes. To enhance the airport slot allocation, this work proposes the study of the problem from a System of Systems Engineering approach (SoSE), both for the primary and secondary scenarios. Through the application of Auction Engineering and Experimental Economics, a set of market mechanisms is proposed to engineer these SoS. This paper presents their high-level formalisation, that will be implemented in future works and assessed according to a set of pre-established key performance indicators.
... Markets are based on supply and demand, which are ultimately founded on economic factors, so they can provide information about how valuable a slot is in economic terms. Besides, a market where the participants maximise their surplus is usually associated with a maximisation of the social welfare [8][9][10]. ...
Airport slot allocation is a combinatorial allocation problem involving different complex and autonomous systems. Nowadays, airport slots are allocated in a two-stage process: primary allocation is performed according to a set of administrative rules and for each airport independently, while secondary allocation is based on trading mechanisms. Several studies have raised inefficiencies in these processes. To enhance the airport slot allocation process we use an auction-based market. More specifically, we present an airport slot allocation mechanism based on a price-setting auction that has been implemented and evaluated by means of Agent-Based Modelling (ABM) and simulation techniques. The solutions obtained using our approach are compared and assessed with the ones obtained using linear programing, showing that market mechanisms can be an efficient alternative to the current administrative procedure.
... Many studies recommend open markets and auction markets for the acquisition of airport slots both in the EU and the US [6], [7], [8], [9], [10], [11]. Works such as [12] propose mechanisms that try to overcome the shortcomings of the typical auctioning procedures by incorporating the concept of social welfare. Another auction system aimed at progressively introducing auctions to replace administrative allocation is presented in [13], but it could involve different prices for slots in the same coordination time interval. ...
ACCESS (www.access-sesar.eu) is a SESAR WPE
project aimed at designing, analysing and assessing alternative
slot allocation mechanisms for primary and secondary allocation
at congested airports. Compared to the current system, mainly
based on administrative regulation and historic rights, ACCESS
is focused on the study of market mechanisms. Market
mechanisms are expected to provide the right incentives for a
more efficient use of the available capacity, but they also raise a
number of concerns. To evaluate the impact of different
mechanisms in terms of a comprehensive set of Key Performance
Indicators, ACCESS applies a scientific approach based on
Auction Engineering to design the Auction Markets, Experiment
Design to structure their analysis, and Agent-Based Modelling
(ABM) and Simulation as the tool to perform Experimental
Economics and test these mechanisms in realistic scenarios. This
paper shows how these methodologies are applied in ACCESS,
using a specific Combinatorial Auction Market as an example.
... Consequently, many studies claim for an open market for the acquisition of airport slots both in any EU member and in the US [5]. Mathematical improvements based on optimisation mechanisms [6], [7], and auction markets have already been proposed [8], [9], [10] but none of them tackle the problem from a SoSE perspective. This have been the motivation to establish a roadmap that will show how to tackle this problem with a SoSE approach and its benefits. ...
... See Madas & Zografos (2006) for an up-to-date review of the current instruments and proposals of enhanced slot allocation procedures. In Arul et al. (2007) a new model for allocating the slots is presented. ...
The internet is providing firms with an increased opportunity to use auctions as a price discovery mechanism for disposing surplus assets in both Business‐to‐Business (B2B) and Business‐to‐Consumer (B2C) environments. While numerous papers have focused on the savings that are attained by electronic auctions vis‐a‐vis conventional (non‐internet‐based) procurement practices in B2B environments, few have offered economic intuition or empirical evidence to gauge the performance of the new price distribution channels available to a seller firm that is ready to exploit the internet in B2B or B2C environment. We develop a stochastic model to compare the expected performance of an online auction approach relative to a fixed (posted or listed) price approach in the presence of the forecast errors that are associated with traffic intensity and the variance in customers' willingness‐to‐pay.
In a one-sided ascending combinatorial auction, bidders place bids on packages of items. When values are interdependent, multi-round auctions are employed to allow price discovery. In such designs, bidders desire feedback on the estimated prices of items and packages in each round. In addition, prices are often used to set the minimum acceptable bid amounts for the next round. Due to the combinatorial nature of the winner determination problem, determining the prices of the individual items is not straightforward. The ascending proxy auction (Ausubel-Milgrom, 2001) has been proposed as a design, where the minimum acceptable bid amounts are a very small increment above the previous high bid on an item or package. These translate to nonlinear and non-anonymous (bidder specific) pricing. When agents are substitutes and the buyer sub-modularity condition is satisfied, the ascending proxy design achieves an efficient outcome at minimum competitive equilibrium prices. But the requirement for an infinitesimally small increment size, results in an auction with a very large number of rounds. In this paper, we propose two alternative linear-pricing schemes that use the game-theoretic concept of the nucleolus to provide price estimates for each item and to determine minimum acceptable bid amounts. We study the effects of such pricing on the length of the auction, the efficiency of the outcome and the prices paid by the winning bidders. We use the linear pricing schemes in an ascending proxy auction framework and benchmark the results against an ascending proxy auction and a faster-to-compute variant of this algorithm that we label the "accelerated proxy auction design". We also compare our results with those obtained using previously proposed linear pricing schemes., for their helpful suggestions and comments. Of course, all errors are our own.
This article reviews some of the major economic issues faced by the FCC in thelast year. It focuses on the application of new analytic techniques at the FCC, andidentifies several areas in which further academic research would be valuable to theFCC.
We introduce a new combinatorial auction format based on a simple, transparent pricing mechanism
tailored for the hierarchical package structure proposed by Rothkopf, Pekeč, and Harstad to avoid computational
complexity [Rothkopf, M., Pekeč, A., Harstad, R., 1998, Computationally manageable combinatorial
auctions. Manage. Sci. 44, 1131–1147]. This combination provides the feedback necessary for bidders in
multi-round auctions to discern winning bidding strategies for subsequent rounds and to coordinate responses
to aggressive package bids. The resulting mechanism is compared to two leading alternatives in a
series of laboratory experiments involving varying degrees of value synergies. Based on these “wind tunnel”
tests the FCC has decided to use hierarchical package bidding in a segment of the upcoming 700 MHz
auction.
The generation of realistic data sets in a Combinatorial Auction may be a challenging problem. Well-formed data sets are very useful in the evaluation of algorithms trying to solve the winner determination problem. In this paper a general data set generation scheme is presented, both from an algorithmic and economic point of view. As a case study, a possible auction setting is discussed where the goods on sale are connections between points in space.
Ongoing research is described for an auction model, a hybrid demand management approach for congested airports. This approach is intended to optimize the use of airport time slots by maximizing passenger throughput with safe capacity, decreasing congestion, and less delay. The two submodels mathematically formulate conflicting optimization problems of efficiency-driven airport regulators and cost-driven airlines. By ranking key factors such as monetary bidding, flight origin-destination pairs, enplanement capability, and airlines' previous investments, a framework is presented that is open to many design alternatives. Two design alternatives are analyzed in a case study of Hartsfield Atlanta International Airport, Georgia, to compare different allocation schemata and resulting airport performance. The performance analysis used a queuing model simulation. By varying weighting coefficients for bid vectors, it is proposed that the effects of administrative coordination and market force on outcomes of the auction process could be monitored to achieve airport-specific benefits. It is also suggested that the conventional auction format that uses monetary bidding alone could lead to potential distortions of the marketplace and fail to meet air transportation officials' concerns about the efficient use of national resources and policy makers' concerns about market structure and competitiveness. Future work will enlist the input from both airlines and airports.
The next generation manufacturing system is conceived to be intelligent enough to take decisions and automatically adjust itself to situations such as variations in production demand and machine breakdowns. The manufacturing control system must have the intelligence to ensure real time operational control by interacting with different manufacturing subsystems. One of the prominent methodologies to deal with the problem of distributed manufacturing systems is the auction-based heuristic control strategy in which various entities bid themselves, accept bids and make selection amongst bids. The present paper addresses the flexible manufacturing system machine-loading problem where job selection and operation allocation on machines are to be performed such that there is a minimization of system unbalance and a maximization of throughput. The methodology of winner determination using the combinatorial auction process is employed to solve the flexible manufacturing system machine-loading problem. In the combinatorial auction, allowing bidding on a combination of assets offers a way to enhance the efficiency of allocating the assets. The performance of the proposed approach is tested on 10 sample problems and the results thus obtained are compared with the existing models in the literature.
In this paper, we present evidence of the need for the specification of property rights associated with airport departure and arrival time slots and then provide the rationale and means for using auctions to allocate such property rights. We provide a historical look at slot allocation in the U.S. and the consequences of prior and current practices on both safety and competition. It is shown that the particular characteristics of aviation slot allocation suggest the need for three types of market mechanisms: an auction of long- term leases of arrival and/or departure slots, a market that supports inter-airline exchange of long-term leases and a near-real-time market that allows for the exchange of slots on a particular day of operation. We describe how certain concepts and tools underlying Collaborative Decision Making (CDM) provide a natural basis for developing the near- real-time market and present a broad overview of the special characteristics of aviation slot auctions and appropriate research topics.
This paper presents our ongoing research on an auction model-a hybrid demand management approach for congested airports. It is intended to optimize the utilization of airport time slots by maximizing passenger throughput within safe capacity, decreasing congestion and delay. The two sub-models mathematically formulate conflicting optimization problems of efficiency-driven airport regulators and cost-driven airlines. By taking many key factors such as flight OD-pair, commercial aircraft size, historical on-time performance, airlines' prior investment and monetary bid into a ranking function with respective weights, we put forward a framework that opens for many design alternatives. Two design alternatives are analyzed in a case study of Hartsfield Atlanta International Airport (ATL) to compare different allocation schemas and the resulting airport performance. The latter was made possible by a queuing model simulation. We propose that by varying these weights, the effects of administrative coordination and market force upon outcomes of the auction process could be monitored to achieve airport-specific desirable results. We also suggest that the conventional auction format that uses monetary bidding alone could lead to potential distortions of the marketplace and fail to meet air transportation officials' concerns in terms of efficient utilization of national resources, and policy makers' concerns in terms of market structure and competitiveness. Future work will enlist the inputs from both airlines and airports.
Many auctions involve the sale of a variety of distinct assets. Examples are airport time slots, delivery routes, network routing, and furniture. Because of complementarities or substitution effects between the different assets, bidders have preferences not just for particular items but for sets of items. For this reason, economic efficiency is enhanced if bidders are allowed to bid on bundles or combinations of different assets. This paper surveys the state of knowledge about the design of combinatorial auctions and presents some new insights. Periodic updates of portions of this survey will be posted to this journal’s Online Supplements web page at http://joc.pubs.informs.org/OnlineSupplements.html.
Most shippers go through an annual auction process of procuring transportation services, leading to an annual contract. This paper argues that the use of combinatorial auctions in this procurement can unlock significant reductions in operating costs for shippers, while protecting carriers from "winning" the lanes that do not fit their network, thus improving carriers' operations as well. Combinatorial auctions account for carriers' economies of scope, which, by many accounts, are more important than economies of scale in transportation operations. Any transportation procurement procedure, however, has also to account for level of service and other non-price variables. Such factors are just as important as price in determining which carrier should serve what lane. These considerations can be incorporated into the combinatorial auction framework easily and holistically. The paper introduces the approach and its potential for creating win/win situations for carriers and shipper. After several years of using this approach it has become the preferred procurement mechanism for leading shippers, with several software providers offering the requisite software.
A sealed-bid combinatorial auction is developed for the allocation of airport time slots to competing airlines. This auction procedure permits airlines to submit various contingency bids for flight-compatible combinations of individual airport landing or take-off slots. An algorithm for solving the resulting set-packing problem yields an allocation of slots to packages that maximizes the system surplus as revealed by the set of package bids submitted. The algorithm determines individual (slot) resource prices which are used to price packages to the winning bidders at levels guaranteed to be no greater (and normally smaller) than the amounts bid. Laboratory experiments with cash motivated subjects are used to study the efficiency and demand revelation properties of the combinatorial auction in comparison with a proposed independent slot primary auction.
The purpose is to design and evaluate, by way of an initial existence proof, the premise that slot allocation via an auction is a possible solution to the air traffic congestion problem surrounding high demand/capacity ratio airports. By demonstrating the existence of such a method for allocating slots at congested airports, this would lead to further research in much greater detail in creating an overall system design of slot allocation that could be implemented. A successful implementation of a slot allocation system would generate capital for air transportation system modernization and reduce delay into and out of the high traffic airports. This in turn is directly correlated to an increase in safety due to a decrease in the number of safe separation conditions that currently occur. To demonstrate potential existence the project is broken down into three primary parts. Several sets of auction rules are used to simulate potential fleet assignment to the airports included within the slot allocation system. Various sets of auction rules are then used as input parameters to generate multiple schedules. Once the schedule is determined a network delay simulation is run to measure delay and demand met by that particular schedule. Finally, the data collected from the simulation runs is analyzed and the results indicates that an auction is a feasible method of allocation for airport time slots for commercial airlines.
Introduction In recent times combinatorial auctions have become an interesting domain for theoretical and applied developments of the electronic market technology. A combinatorial auction allows the simultaneous selling of several items and each participant to the auction may bid for bundles of items. When items in a bid are all di#erent the auction is said a Single Unit Combinatorial Auction (SUCA), while when a bid may specify a number of units of a given item we call it a Multi-Unit Combinatorial Auction (MUCA). The bid taker's objective is to find that set of bids which maximizes his total revenue. It has been shown that the problem, known as Winner Determination Problem, also for the special case in which each item is available in single units, is NP-hard ([4]). Up to now the bulk of research work on this subject has been focused on SUCA while a limited number of papers are available on the problem of Winner Determination in a MUCA (see, for instance, [2], [3] and [5]). For a co
Many auctions involve the sale of a variety of distinct assets. Ex- amples are airport time slots, delivery routes, network routing and fur- niture. Because of complementarities or substitution effects between the different assets, bidders have preferences not just for particular items but for sets of items. For this reason, economic efficiency is enhanced if bidders are allowed to bid on bundles or combinations of different assets. This note outlines some of the underlying theory and identifies some research questions. The reader interested in more details on research in this are should consult the survey paper by de Vries and myself on combinatorial auctions. I am greatful for use- ful conversations with Sushil Bikhchandani, Sven de Vries, Peter Eso, Tuomas Sandholm, James Schummer and Subhash Suri.
An auction designer faces many questions. Among the questions are what precisely is to be sold, who may bid, will there be multiple rounds of bidding, what kinds of payments will be made and which are biddable, how will the bids be compared, how will it be decided if a transaction occurs, how will the price be set, how will sales of multiple items be handled, and what information will be revealed and when. Different academic disciplines have contributed to answering these questions. In addition to OR/MS, these include engineering, economics, sociology, and computer science.
This paper presents the concept of optimization-based procurement for transportation services. The approach allows both the shipper and carriers to benefit through the use of a collaborative approach to securing and managing a strategic relationship. Because the shipper's assignment problem involves a combinatorial number of choices and cannot be easily executed manually, the procurement process benefits strongly from the use of optimization. The authors introduce the optimization-based procurement process, briefly analyze the theoretical issues, and discuss lessons learned from its application in practice over the last several years.
Combinatorial auctions have two features that greatly affect their design: computational complexity of winner determination and opportunities for cooperation among competitors. Dealing with these forces trade-offs between desirable auction properties such as allocative efficiency, revenue maximization, low transaction costs, fairness, failure freeness, and scalability. Computational complexity can be dealt with algorithmically by relegating the computational burden to bidders, by maintaining fairness in the face of computational limitations, by limiting biddable combinations, and by limiting the use of combinatorial bids. Combinatorial auction designs include single-round, first-price sealed bidding, Vickrey-Clarke-Groves (VCG) mechanisms, uniform and market-clearing price auctions, and iterative combinatorial auctions. Combinatorial auction designs must deal with exposure problems, threshold problems, ways to keep the bidding moving at a reasonable pace, avoiding and resolving ties, and controlling complexity.
Combinatorial auctions (CAs) have recently generated significant interest as an automated mechanism for buying and selling
bundles of goods. They are proving to be extremely useful in numerous e-business applications such as e-selling, e-procurement,
e-logistics, and B2B exchanges. In this article, we introduce combinatorial auctions and bring out important issues in the
design of combinatorial auctions. We also highlight important contributions in current research in this area. This survey
emphasizes combinatorial auctions as applied to electronic business situations.
This paper studies the solution of several types of combinatorial (double) auctions. Such auctions have recently been used in business-to-business trading in a centralized marketplace, or in multi-agent coordination systems in artificial intelligence. When the goods are indivisible, solving the winner determination problem (WDP) is an integer programming problem and NP-hard in its general form. We show that a general combinatorial double auction can be reduced to a combinatorial single-sided auction, which is a multi-dimensional knapsack problem.Next, we compare the performance of several solution approaches for this type of problem. We contrast the branch-and-bound method with the intelligent search method proposed separately in three well-referenced papers. We found that theoretically the LP relaxation bounds always dominate the bounds used in the specialized intelligent searches. We also found empirically that the performance of this branch-and-bound method is superior to the specialized search methods that have been proposed for this class of problems.
Trucking companies (carriers) are increasingly facing combinatorial auctions conducted by shippers seeking contracts for their transportation needs. The bid valuation and construction problem for carriers facing these combinatorial auctions is very difficult and involves the computation of a number of NP-hard sub problems. In this paper we examine computationally tractable approximation methods for estimating these values and constructing bids. The benefit of our approximation method is that it provides a way for carriers to discover their true costs and construct optimal or near optimal bids by solving a single NP-hard problem. This represents a significant improvement in computational efficiency. We examine our method both analytically and empirically using a simulation based analysis.
Combinatorial auctions, that is, auctions where bidders can bid on combinations of items, tend to lead to more efficient allocations than traditional auction mechanisms in multi-item auctions where the agents' valuations of the items are not additive. However, determining the winners so as to maximize revenue is -complete. First, we analyze existing approaches for tackling this problem: exhaustive enumeration, dynamic programming, and restricting the allowable combinations. Second, we study the possibility of approximate winner determination, proving inapproximability in the general case, and discussing approximation algorithms for special cases. We then present our search algorithm for optimal winner determination. Experiments are shown on several bid distributions which we introduce. The algorithm allows combinatorial auctions to scale up to significantly larger numbers of items and bids than prior approaches to optimal winner determination by capitalizing on the fact that the space of bids is sparsely populated in practice. The algorithm does this by provably sufficient selective generation of children in the search tree, by using a secondary search for fast child generation, by using heuristics that are admissible and optimized for speed, and by preprocessing the search space in four ways. Incremental winner determination and quote computation techniques are presented.
raditional development of large-scale information systems is based on centralized infor- mation processing and decision making. With increasing competition, shorter product life-cycle, and growing uncertainties in the marketplace, centralized systems are inadequate in processing information that grows at an explosive rate and are unable to make quick re- sponses to real-world situations. Introducing a decentralized information system in an orga- nization is a challenging task. It is often intertwined with other organizational processes. The goal of this research is to outline a new approach in developing a supply chain information system with a decentralized decision making process. Particularly, we study the incentive structure in the decentralized organization and design a market-based coordination system that is incentive aligned, i.e., it gives the participants the incentives to act in a manner that is beneficial to the overall system. We also prove that the system monotonically improves the overall organizational performance and is goal congruent. (Decentralized Information System; Coordination Mechanism; Incentive; Auction; Complementarity; Supply Chain)
We study dominant strategy implementation in a variant of the canonical public good provision model, as proposed by Borgers and Postl (2009). In this set up, we fully characterize the set of budget-balanced dominant strategy deterministric mechanisms, which are simple threshold rules. For probabilistic mechanisms that are continuously differentiable we provide a necessary and sufficient condition for dominant strategy implementation. When allowing for discontinuities in the mechanism, our necessary condition remains valid, but additional requirements must be met in order to ensure sufficiency.
This paper examines the efficiency and practicality of airport slot constraints using a deterministic bottleneck model of landing and takeoff queues. It adapts this congestion pricing model to determine the optimal timing and quantity of slot permits for any number of slot windows. Aircraft choose their optimal operating times subject to the slot constraints, and airport queues adjust endogenously. The number and length of slot windows affects the congestion levels and efficiency gains. The atomistic bottleneck model is extended to include self-internalizing dominant traffic and atomistic fringe traffic. The model raises questions about the implementation of slot constraints that do not arise in standard congestion models. The theory explains Daniel's (2009a) empirical findings that slot-constraints at Toronto are ineffective and suggests that recent proposals for slot constraints at US airports would be similarly ineffective. Effective slot constraints require many narrow slot windows, making slot auctions or markets difficult to implement.
When an auction of multiple items is performed, it is often desirable to allow bids on combinations of items, as opposed to only on single items. Such an auction is often called "combinatorial ", and the exponential number of possible combinations results in computational intractability of many aspects regarding such an auction. This paper considers two of these aspects: the bidding language and the allocation algorithm. First we consider which kinds of bids on combinations are allowed and how, i.e. in what language, they are specified. The basic tradeoff is the expressibility of the language versus its simplicity. We consider and formalize several bidding languages and compare their strengths. We prove exponential separations between the expressive power of different languages, and show that one language, "OR-bids with phantom items", can polynomially simulate the others. We then consider the problem of determining the best allocation -- a problem known to be computationally intractable. We suggest an approach based on Linear Programming (LP) and motivate it. We prove that the LP approach finds an optimal allocation if and only if prices can be attached to single items in the auction. We pinpoint several classes of auctions where this is the case, and suggest greedy and branch-and-bound heuristics based on LP for other cases. 1
We propose a heuristic for allocation in combinatorial auctions. We first run an approximation algorithm on the linear programming relaxation of the combinatorial auction. We then run a sequence of greedy algorithms, starting with the order on the bids determined by the approximate linear program and continuing in a hill-climbing fashion using local improvements in the order of bids. We have implemented the algorithm and have tested it on the complete corpus of instances provided by Vohra and de Vries as well as on instances drawn from the distributions of Leyton-Brown, Pearson, and Shoham. Our algorithm typically runs two to three orders of magnitude faster than the reported running times of Vohra and de Vries, while achieving an average approximation error of less than 1%. This algorithm can provide, in less than a minute of CPU time, excellent solutions for problems with over 1000 items and 10,000 bids. We thus believe that combinatorial auctions for most purposes face no practical computational hurdles. 1.
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