577 research outputs found
An Agent Based Market Design Methodology for Combinatorial Auctions
Auction mechanisms have attracted a great deal of interest and have been used in diverse e-marketplaces. In particular, combinatorial auctions have the potential to play an important role in electronic transactions. Therefore, diverse combinatorial auction market types have been proposed to satisfy market needs. These combinatorial auction types have diverse market characteristics, which require an effective market design approach. This study proposes a comprehensive and systematic market design methodology for combinatorial auctions based on three phases: market architecture design, auction rule design, and winner determination design. A market architecture design is for designing market architecture types by Backward Chain Reasoning. Auction rules design is to design transaction rules for auctions. The specific auction process type is identified by the Backward Chain Reasoning process. Winner determination design is about determining the decision model for selecting optimal bids and auctioneers. Optimization models are identified by Forward Chain Reasoning. Also, we propose an agent based combinatorial auction market design system using Backward and Forward Chain Reasoning. Then we illustrate a design process for the general n-bilateral combinatorial auction market. This study serves as a guideline for practical implementation of combinatorial auction markets design.Combinatorial Auction, Market Design Methodology, Market Architecture Design, Auction Rule Design, Winner Determination Design, Agent-Based System
Social Value Propagation for Supply Chain Formation
Supply Chain Formation is the process of determining the participants in a supply chain, who will exchange what with whom, and
the terms of the exchanges. Decentralized supply chain formation appears as a highly intricate task because agents only possess local information, have limited knowledge about the capabilities of other agents, and prefer to preserve privacy. State-of-the-art decentralized supply chain formation approaches can either: (i) #12;find supply chains of high value at the expense of high resources usage; or (ii) fi#12;nd supply chains of low value with low resources usage. This work presents chainme, a novel decentralized supply chain formation algorithm. Our results show that chainme fi#12;nds supply chains with higher value than state-of-the-art decentralized algorithms
whilst decreasing the amount of resources required from one up to four orders of magnitude.Peer Reviewe
Auctions and bidding: A guide for computer scientists
There is a veritable menagerie of auctions-single-dimensional, multi-dimensional, single-sided, double-sided, first-price, second-price, English, Dutch, Japanese, sealed-bid-and these have been extensively discussed and analyzed in the economics literature. The main purpose of this article is to survey this literature from a computer science perspective, primarily from the viewpoint of computer scientists who are interested in learning about auction theory, and to provide pointers into the economics literature for those who want a deeper technical understanding. In addition, since auctions are an increasingly important topic in computer science, we also look at work on auctions from the computer science literature. Overall, our aim is to identifying what both these bodies of work these tell us about creating electronic auctions. © 2011 ACM.This work was funded in part by HP under the “Always on” grant, by NSF IIS-0329037 “Tools and Techniques for Automated Mechanism Design”, and by IEA (TIN2006-15662-C02-01), OK (IST-4-027253-STP), eREP(EC-FP6-CIT5-28575) and Agreement Technologies (CONSOLIDER CSD2007-0022, INGENIO 2010).Peer Reviewe
Combinatorial auctions for electronic business
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
Hybrid Models for Learning to Branch
A recent Graph Neural Network (GNN) approach for learning to branch has been
shown to successfully reduce the running time of branch-and-bound algorithms
for Mixed Integer Linear Programming (MILP). While the GNN relies on a GPU for
inference, MILP solvers are purely CPU-based. This severely limits its
application as many practitioners may not have access to high-end GPUs. In this
work, we ask two key questions. First, in a more realistic setting where only a
CPU is available, is the GNN model still competitive? Second, can we devise an
alternate computationally inexpensive model that retains the predictive power
of the GNN architecture? We answer the first question in the negative, and
address the second question by proposing a new hybrid architecture for
efficient branching on CPU machines. The proposed architecture combines the
expressive power of GNNs with computationally inexpensive multi-linear
perceptrons (MLP) for branching. We evaluate our methods on four classes of
MILP problems, and show that they lead to up to 26% reduction in solver running
time compared to state-of-the-art methods without a GPU, while extrapolating to
harder problems than it was trained on.Comment: Preprint. Under revie
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