Combinatorial Auctions: A Survey

Market Design for Renewable Energy Auctions: An Analysis of Alternative Auction Formats

Auctions where landholders submit conservation projects for consideration in return for payment have recently gained popularity. Flexible versions of these, combinatorial auctions, which allow for the simultaneous submission of bids on different combinations of projects, have recently been tested for conservation purposes. Combinatorial auctions allow bidders to exploit synergies in the execution of multiple conservation activities while the auction mechanism stimulates competition among potential participants, enabling the auctioneer (or government) to secure a cost-effective set of conservation projects. Combinatorial auctions have the potential to improve outcomes beyond what is possible with the simple auctions explored in trials over the last decade in many parts of Australia. This article reviews the state of the art in the design of combinatorial auctions with a particular focus on conservation auctions. Key design issues identified are the problem of determining the winning bid, pricing formats, and iterative bidding formats where bidders are able to revise their bids before a final selection is made.

Traditional auction mechanisms support price negotiations on a single item. The Internet allows for the exchange of much more complex offers in real-time. This is one of the reasons for much research on multidimensional auction mechanisms allowing negotiations on multiple items, multiple units, or multiple attributes of an item, as they can be regularly found in procurement. Combinatorial auctions, for example, enable suppliers to submit bids on bundles of items. A number of laboratory experiments has shown high allocative efficiency in markets with economies of scope. For suppliers it is easier to express cost savings due to bundling (e. g., decreased transportation or production costs). This can lead to significant savings in total cost of the procurement manager. Procurement negotiations exhibit a number of particularities: It is often necessary to consider qualitative attributes or volume discounts in bundle bids. These complex bid types have not been sufficiently analyzed. The winner determination problem requires the consideration of a number of additional business constraints, such as limits on the spend on a particular supplier or the number of suppliers. Iterative combinatorial auctions have a number of advantages in practical applications, but they also lead to new problems in the determination of ask prices. In this paper, we will discuss fundamental problems in the design of combinatorial auctions and the particularities of procurement applications.Reprint of an article from WIRTSCHAFTSINFORMATIK 47(2)2005:126–134.

Activity rules have emerged in recent years as an important aspect of practical auction design. The role of an activity rule in an iterative auction is to suppress strategic behavior by bidders and promote simple, continual, meaningful bidding and thus, price discovery. These rules find application in the design of iterative combinatorial auctions for real world scenarios, for example in spectrum auctions, in airline landing slot auctions, and in procurement auctions. We introduce the notion of strong activity rules, which allow simple, consistent bidding strategies while precluding all behaviors that cannot be rationalized in this way. We design such a rule for auctions with budget-constrained bidders, i.e., bidders with valuations for resources that are greater than their ability to pay. Such bidders are of practical importance in many market environments, and hindered from bidding in a simple and consistent way by the commonly used revealed-preference activity rule, which is too strong in such an environment. We consider issues of complexity, and provide two useful forms of information feedback to guide bidders in meeting strong activity rules. As a special case, we derive a strong activity rule for non-budget-constrained bidders. The ultimate choice of activity rule must depend, in part, on beliefs about the types of bidders likely to participate in an auction event because one cannot have a rule that is simultaneously strong for both budget-constrained bidders and quasi-linear bidders.

Combinatorial auctions are multiple-item auctions in which bidders may place bids on any package (subset) of goods. This additional expressibility produces benefits that have led to combinatorial auctions becoming extremely important both in practice and in theory. In the computer science community, auction design has focused primarily on computational practicality and incentive compatibility. The latter concerns mechanisms that are resistant to bidders misrepresenting themselves via a single false identity; however, with modern forms of bid submission, such as electronic bidding, other types of cheating have become feasible. Prominent amongst them is false-name bidding; that is, bidding under pseudonyms. For example, the ubiquitous Vickrey-Clarke-Groves (VCG) mechanism is incentive compatible and produces optimal allocations, but it is not false-name-proof–bidders can increase their utility by submitting bids under multiple identifiers. Thus, there has recently been much interest in the design and analysis of false-name-proof auction mechanisms. These false-name-proof mechanisms, however, have polynomially small efficiency guarantees: they can produce allocations with very low economic efficiency/social welfare. In contrast, we show that, provided the degree to which different goods are complementary is bounded (as is the case in many important, practical auctions), the VCG mechanism gives a constant efficiency guarantee. Constant efficiency guarantees hold even at equilibria where the agents bid in a manner that is not individually rational. Thus, while an individual bidder may personally benefit greatly from making false-name bids, this will have only a small detrimental effect on the objective of the auctioneer: maximizing economic efficiency. So, from the auctioneer's viewpoint the VCG mechanism remains preferable to false-name-proof mechanisms.

Recent advances in Fourier analysis have brought new tools to efficiently represent and learn set functions. In this paper, we bring the power of Fourier analysis to the design of combinatorial auctions (CAs). The key idea is to approximate bidders' value functions using Fourier-sparse set functions, which can be computed using a relatively small number of queries. Since this number is still too large for practical CAs, we propose a new hybrid design: we first use neural networks (NNs) to learn bidders’ values and then apply Fourier analysis to the learned representations. On a technical level, we formulate a Fourier transform-based winner determination problem and derive its mixed integer program formulation. Based on this, we devise an iterative CA that asks Fourier-based queries. We experimentally show that our hybrid ICA achieves higher efficiency than prior auction designs, leads to a fairer distribution of social welfare, and significantly reduces runtime. With this paper, we are the first to leverage Fourier analysis in CA design and lay the foundation for future work in this area. Our code is available on GitHub: https://github.com/marketdesignresearch/FA-based-ICAs.

In this chapter, a model for using Multi Intelligent Agents and Swarm Intelligence for trusted routing in mobile ad-hoc networks (MANETs) is presented. The new algorithm called TARA is proved more efficient in different ways than the existing protocols. TARA uses a local trust evaluation method to indicate an objective trust value for each node within the network depending on its forwarding behavior; therefore, a multi agent system is hosted on each node and monitors its forwarding behavior. Both the number and total size of packets being forwarded are considered. The trust value of each node is directly applied to the route as it is being built, so there is no need to propagate the trust values like other trusted protocols. Ant Colony Optimization (ACO) is used to find the best route for delivery and the processes of strengthening and evaporation of the route pheromone value are applied. Simulation using a random-way-point mobility model with different parameters had been carried out and comparison with other protocols complexity and performance was presented.

Sleep and wake-up scheduling of sensor nodes is an efficient solution to prolong the network lifetime. However, existing scheduling algorithms may significantly decrease the number of active nodes so that the network may be intermittently connected. In light of this, traditional geographic routing protocols are inappropriate to obtain low latency routes due to route discovery and data forwarding latency. Recently, Lu Su et al. have proposed an ODML routing scheme that finds low latency routes in intermittently-connected sensor networks by using RREQ and RREP messages [9]. Nevertheless, ODML does not consider the latency of RREP and has a high routing overhead. This paper proposes a novel Multicandidate Greedy Routing (MGR) scheme that makes the best effort to find minimum latency routes in wireless sensor networks. In MGR, each source node sends an RREQ to a set of first wake-up forwarder candidates and selects a route with minimum estimated delivery latency based on their replies. Simulation results demonstrate that our proposed scheme performs better than the distance-based greedy forwarding and ODML in terms of delivery latency and routing overhead.

Often, an outcome must be chosen on the basis of the preferences reported by a group of agents. The key difficulty is that the agents may report their preferences insincerely to make the chosen outcome more favorable to themselves. Mechanism design is the art of designing the rules of the game so that the agents are motivated to report their preferences truthfully, and a desirable outcome is chosen. In a recently proposed approach---called automated mechanism design ---a mechanism is computed for the preference aggregation setting at hand. This has several advantages, but the downside is that the mechanism design optimization problem needs to be solved anew each time. Unlike the earlier work on automated mechanism design that studied a benevolent designer, in this paper we study automated mechanism design problems where the designer is self-interested. In this case, the center cares only about which outcome is chosen and what payments are made to it. The reason that the agents' preferences are relevant is that the center is constrained to making each agent at least as well off as the agent would have been had it not participated in the mechanism. In this setting, we show that designing optimal deterministic mechanisms is NP-complete in two important special cases: when the center is interested only in the payments made to it, and when payments are not possible and the center is interested only in the outcome chosen. We then show how allowing for randomization in the mechanism makes problems in this setting computationally easy. Finally, we show that the payment-maximizing AMD problem is closely related to an interesting variant of the optimal (revenue-maximizing) combinatorial auction design problem, where the bidders have "best-only" preferences. We show that here, too, designing an optimal deterministic auction is NP-complete, but designing an optimal randomized auction is easy.

Canada Post’s lettermail volumes are plummeting, largely due to the explosion of electronic communication, with no evident sign of stabilizing. E-commerce parcel deliveries are on the rise, but not nearly at the rate necessary to offset the decline in lettermail, and there are many private courier companies competing for that business. Meanwhile, even as the number of Canadian home addresses continues to increase, Canada Post’s plan to end the remnants of door-to-door home delivery, had to be halted in light of the new Liberal government’s promise to maintain the service. The extraordinary disruption that electronic media has caused to the model of stateowned postal services, with their mandate to provide universal delivery, may seem dire. And the threat is indeed urgent. But there are solutions to help Canada Post remain healthy in reforms that have occurred to postal systems elsewhere. This does not necessarily mean immediate privatization (although that has been achieved with some success in Europe): The burden of universal service obligations in a country as expansive and minimally populated as Canada is, could make it difficult for the government to realize appropriate value in selling Canada Post. But if the Liberal government intends to help Canada Post endure in this environment, it should allow the corporation to introduce some basic elements of competition and marketbased reform. The reality is that most Canadian mail today is sent by large firms to customers and other businesses. And most mail is delivered in urban areas, where delivery costs are lowest. But because Canada Post is required to charge identical prices to all customers, urban households essentially help subsidize the postage costs of big business and rural recipients. This need not be the case: Canada Post would be more successful if it could charge varying rates (capped at a maximum) based on the type of sender, volume, and the mail’s destination. One could also imagine scenarios where recipients pay an annual fee for different levels of service, paying extra for door-to-door delivery for example. Canada Post currently allows its clients to compete with it for the sortation of mail (offering discounts for firms willing to pre-sort mail), and there is much more room for competition in the collection, transport and sorting of mail. Already, it is likely that Canada Post has too many sorting facilities, given the advent of new sorting technologies; outsourcing certain upstream operations could help it further reduce its infrastructure and labour costs. There is also a case to be made for Canada Post reducing its delivery frequency and delivery times, especially in higher-cost rural areas. Surveys indicate that Canadians would be fine with that. Allowing competition in delivery, on the other hand, comes with risks of rivals willing to snap up delivery routes in dense urban networks, leaving Canada Post with an even less profitable model in being left to deliver its (and competitors’) products in only high-cost areas. This can be offset, however, by requiring competitors to assume some of the incumbent’s universal service obligations, or at least paying a tax to compensate Canada Post for its obligations. Ensuring these reforms remain compatible with the financial viability of the incumbent would be helped by setting up an independent regulator to ensure the maintenance of a level playing field and to separate the influence of politics from decision-making. In the current era, however, the idea that universal service obligations should be exclusive to mail carriers seems antiquated. It is only rational that the independent regulator be charged with overseeing that universal service obligations are shared between telecom services and mail services.

The effects of recycling loops in food waste management in Japan: Based on the environmental and economic evaluation of food recycling

This study designs a new market for fractional ownership of autonomous vehicles (AVs), in which an AV is co‐leased by a group of individuals. We present a practical iterative auction based on the combinatorial clock auction to match the interested customers together and determine their payments. In designing such an auction, we consider continuous‐time items (time slots) that are defined by bidders and naturally exploit driverless mobility of AVs to form co‐leasing groups. To relieve the computational burdens of both bidders and the auctioneer, we devise user agents who generate packages and bid on behalf of bidders. Through numerical experiments using the California 2010–2012 travel survey, we test the performance of the auction design. We also compare various bidding strategies and study the effect of activity rules on the bidders' payoffs. We find that the designed activity rules successfully remove the strategic behavior of bidders. We also find that core‐selecting payment rule brings the largest revenue to the auctioneer in most cases.

2013: Busy year for Journal of Optometry

This paper uses a general equilibrium model to simulate both the effects of a preferential capital-gains tax rate on total income tax revenues and the effects of a revenue-neutral substitution between a capital gains preference and marginal income tax rates on economic efficiency and the distribution of income. In the simulations, a capital gains preference increases efficiency by reducing tax distortions between untaxed assets (household and state and local capital) and taxable business sector assets and between realized and unrealized capital gains (the "lock-in" effect), but reduces efficiency by increasing tax distortions between corporate dividends and retained earnings and between financial assets that produce capital gain income and those that produce ordinary income. Because the model treats aggregate factor supplies as fixed, however, the simulations do not capture the efficiency gain from reducing the tax distortion between current and future consumption or the loss from increasing the tax distortion between current consumption and leisure (or untaxed labor).

Delay/Disruption Tolerant Networking (DTN) architecture adopts the concept of intermittent networks that may suffer frequent disconnections, with the possibility of never having end-to-end connectivity between the source and destination over a given period of time. Therefore, the design of protocols for those networks becomes a unique challenge. Routing in DTNs is one of the key components and remains open for discussion. In this paper we treat the routing for anycast delivery that is useful in situations where a host, applications or users wish to locate a host which supports a particular service. However, if several servers support the service, any of these servers can be used. Then we implement a routing algorithm using genetic algorithm (GA), because the route and destination decision influence many parameters simultaneously. Our simulation results have shown that the routing using GA performs better than the shortest path algorithm.