Chain: A Dynamic Double Auction Framework for Matching Patient Agents

In this paper we present and evaluate a general framework for the design of truthful auctions for matching agents in a dynamic, two-sided market. A single commodity, such as a resource or a task, is bought and sold by multiple buyers and sellers that arrive and depart over time. Our algorithm, Chain, provides the first framework that allows a truthful dynamic double auction (DA) to be constructed from a truthful, single-period (i.e. static) double-auction rule. The pricing and matching method of the Chain construction is unique amongst dynamic-auction rules that adopt the same building block. We examine experimentally the allocative efficiency of Chain when instantiated on various single-period rules, including the canonical McAfee double-auction rule. For a baseline we also consider non-truthful double auctions populated with zero-intelligence plus"-style learning agents. Chain-based auctions perform well in comparison with other schemes, especially as arrival intensity falls and agent valuations become more volatile

A Free Exchange e-Marketplace for Digital Services

The digital era is witnessing a remarkable evolution of digital services. While the prospects are countless, the e-marketplaces of digital services are encountering inherent game-theoretic and computational challenges that restrict the rational choices of bidders. Our work examines the limited bidding scope and the inefficiencies of present exchange e-marketplaces. To meet challenges, a free exchange e-marketplace is proposed that follows the free market economy. The free exchange model includes a new bidding language and a double auction mechanism. The rule-based bidding language enables the flexible expression of preferences and strategic conduct. The bidding message holds the attribute-valuations and bidding rules of the selected services. The free exchange deliberates on attributes and logical bidding rules for automatic deduction and formation of elicited services and bids that result in a more rapid self-managed multiple exchange trades. The double auction uses forward and reverse generalized second price auctions for the symmetric matching of multiple digital services of identical attributes and different quality levels. The proposed double auction uses tractable heuristics that secure exchange profitability, improve truthful bidding and deliver stable social efficiency. While the strongest properties of symmetric exchanges are unfeasible game-theoretically, the free exchange converges rapidly to the social efficiency, Nash truthful stability, and weak budget balance by multiple quality-levels cross-matching, constant learning and informs at repetitive thick trades. The empirical findings validate the soundness and viability of the free exchange

Matching mechanisms for two-sided shared mobility systems

Shared mobility systems have gained significant attention in the last few decades due, in large part, to the rise of the service-based sharing economy. In this thesis, we study the matching mechanism design of two-sided shared mobility systems which include two distinct groups of users. Typical examples of such systems include ride-hailing platforms like Uber, ride-pooling platforms like Lyft Line, and community ride-sharing platforms like Zimride. These two-sided shared mobility systems can be modeled as two-sided markets, which need to be designed to efficiently allocate resources from the supply side of the market to the demand side of the market. Given its two-sided nature, the resource allocation problem in a two-sided market is essentially a matching problem. The matching problems in two-sided markets present themselves in decentralized and dynamic environments. In a decentralized environment, participants from both sides possess asymmetric information and strategic behaviors. They may behave strategically to advance their own benefits rather than the system-level performance. Participants may also have their private matching preferences, which they may be reluctant to share due to privacy and ethical concerns. In addition, the dynamic nature of the shared mobility systems brings in contingencies to the matching problems in the forms of, for example, the uncertainty of customer demand and resource availability. In this thesis, we propose matching mechanisms for shared mobility systems. Particularly, we address the challenges derived from the decentralized and dynamic environment of the two-sided shared mobility systems. The thesis is a compilation of four published or submitted journal papers. In these papers, we propose four matching mechanisms tackling various aspects of the matching mechanism design. We first present a price-based iterative double auction for dealing with asymmetric information between the two sides of the market and the strategic behaviors of self-interested agents. For settings where prices are predetermined by the market or cannot be changed frequently due to regulatory reasons, we propose a voting-based matching mechanism design. The mechanism is a distributed implementation of the simulated annealing meta-heuristic, which does not rely on a pricing scheme and preserves user privacy. In addition to decentralized matching mechanisms, we also propose dynamic matching mechanisms. Specifically, we propose a dispatch framework that integrates batched matching with data-driven proactive guidance for a Uber-like ride-hailing system to deal with the uncertainty of riders’ demand. By considering both drivers’ ride acceptance uncertainty and strategic behaviors, we finally propose a pricing mechanism that computes personalized payments for drivers to improve drivers' average acceptance rate in a ride-hailing system

Truthful Double Auction Mechanisms for Heterogeneous Spectrums and Spectrum Group-Buying

Auction has been widely used to spectrum allocation. Most of the previous works supposed that all the spectrums are identical. However, in reality, spectrums are quite different in different locations and frequencies. Recently, some works studied the double auction mechanism for heterogeneous spectrums. But their schemes are based on the assumption of “single-channel request”. To be more realistic, each seller and buyer will bid at least one channel. The previous schemes will not work under multi-channel assumption. In this thesis, I proposed a truthful multi-channel double auction mechanism for heterogeneous spectrums. Our scheme allows sellers and buyers to sell or buy multi-channels for heterogeneous spectrums. We introduce a novel virtual grouping method to split sellers and buyers. We proved that the proposed scheme satisfies the economic properties: truthfulness, individual rationality and budget balance. Simulation results confirmed that our method achieves high auction efficiency and auction revenue. Beyond the double auction for heterogeneous spectrums, recent spectrum auction results have shown that small network providers cannot benefit from the auction directly because of the high price asked by the spectrum holders. Therefore, in this thesis, we proposed a truthful group buying-based double auction mechanism for cognitive radio networks. There are two single-round auction in our method. The first one is between secondary users and secondary access point, in which the secondary access point is the seller and the secondary users are the buyers. We call it the outer auction. The outer auction is based on single-sided buyer-only auction. The other one is between the secondary access points and the spectrum holders, in which the secondary access points are the buyers and the spectrum holders are the sellers. We refer to it as the inner auction. In the inner auction, we apply the double auction mechanism. We proved that our scheme satisfies the economic properties. At last, we proposed a truthful multi-channel double auction mechanism for spectrum group-buying. Since both sellers and buyers would require to trade multiple channels at the same time. No existing designs can meet multi-channel and group-buying requirements simultaneously. To solve this problem, we introduce a novel group splitting and budget calculation algorithm in the outer auction. We apply a proper winner determination and pricing mechanism in the inner auction. This scheme satisfies the economic properties as well

Truthful Trading in Local Energy Markets

With the increasing share of renewable and thus volatile distributed generationworldwide, small-scale energy producers, prosumers and consumers will become more and more involved in the overall energy system. These small-scale actors were formerly excluded from the energy market, as legislative restrictions about generation size and legal stipulations prohibited them from actively taking part in the bidding process. While DERs of intermittent nature, such as PV installations already constitute a significant part of the generation mix, the wholesale electricity markets have not been designed taking their characteristics (production variability, low predictability, zero marginal cost of generation and strong site-specificity) into account, thus making their market integration harder. Local electricity markets (LEMs) solve this issue by providing a local market platform to residential actors within a community. They empower small scale electricity producers, prosumers, and consumers and offer economic incentives for creating local electricity balances. Yet, definitions of LEMs, their concepts and market mechanisms are mostly case driven instead of comparative. Furthermore, mechanisms which induce truthful bidding from market participants have received little attention within the context of residential LEMs. This thesis attempts to address these gaps by comparing several truthful double auction mechanisms and proposing a market mechanism framework suitable for residential LEMs. A Monte Carlo simulation is conducted to compare mechanism performance indicators under various LEM scenarios. Main performance indicators include the quantity of energy traded locally, gains-from-trade between market participants and total revenue received by the market operator. Finally, recommendations on capturing the value of implementing truthful mechanisms are made for potential LEM stakeholders.Electrical Engineering | Sustainable Energy Technolog