1,454 research outputs found

    A Comparative Study of Two Combinatorial Reverse Auction Models

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    Online group-buying is one of the most innovative business models employed by many companies. From the perspective of buyers, quantity based discounts provide a huge incentive to form coalitions and take advantage of lower prices without ordering more than their actual demand. Traditional group-buying mechanisms are usually based on a single item and uniform cost sharing. One way to reduce the cost for acquiring the required items is to take into account the complementarities between items provided by the sellers. By holding a combinatorial reverse auction, the total cost to acquire the required items will be significantly reduced due to complementarities between items. However, combinatorial reverse auctions suffer from high computational complexity. If there are multiple buyers, there are two different business models for procurement based on combinatorial reverse auctions: (1) independent combinatorial reverse auctions: each buyer may hold a combinatorial reverse auction independently and (2) combinatorial reverse auctions based on group buying: multiple buyers delegate the auction to a group buyer and the group buyer holds only one combinatorial reverse auction for all the buyers. In developing an effective tool to support the decision of multiple buyers’ procurement, a comparative study on the performance and efficiency of these two different business models is needed. In this paper, we compare the performance as well as the computational efficiency for these two combinatorial reverse auction models. Our analysis indicates that group buying combinatorial reverse auction outperforms multiple separate combinatorial reverse auctions not only in performance but also in efficiency

    Combinatorial auctions for electronic business

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    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

    A theoretical and computational basis for CATNETS

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    The main content of this report is the identification and definition of market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. These build the theoretical foundation for the work within the following two years of the CATNETS project. --Grid Computing

    Transportation service procurement using combinatorial auctions

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    Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2003.Includes bibliographical references (leaves 39-40).Auction is a mechanism of selling distinct assets that can be both physical objects and virtual objects. Examples of virtual objects are the rights to use assets like airport time slots and FCC spectrum, or to service truckload delivery routes in a transportation network. Under some situations bidding on combinations of objects can render lower total price compare with bidding the objects one at a time, and the auction that allows bidders to bid on combinations of different assets are called combinatorial auctions. With shipper being the auctioneer and carriers being the bidders, combinatorial auction has become increasingly important in the transportation service procurement domain, due to its mechanism to align shipper s procurement interest with carrier transportation service cost structure, which in turn lowers shippers total procurement cost. The thesis provides a comprehensive review of the use of conditional bidding within a transportation combinatorial auction framework. The thesis first describes the general forms of the transportation services available, and discusses the economics of motor carriers that provide LTL and TL services. It then illustrates the basic optimization technique of conditional bidding for TL service procurement and discusses the information technologies that enable the optimization-based procurement and the actual application of the method in the real world.by XiaoPing Chen.M.Eng.in Logistic

    A heuristic approach for the allocation of resources in large-scale computing infrastructures

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    An increasing number of enterprise applications are intensive in their consumption of IT, but are infrequently used. Consequently, organizations either host an oversized IT infrastructure or they are incapable of realizing the benefits of new applications. A solution to the challenge is provided by the large-scale computing infrastructures of Clouds and Grids which allow resources to be shared. A major challenge is the development of mechanisms that allow efficient sharing of IT resources. Market mechanisms are promising, but there is a lack of research in scalable market mechanisms. We extend the Multi-Attribute Combinatorial Exchange mechanism with greedy heuristics to address the scalability challenge. The evaluation shows a trade-off between efficiency and scalability. There is no statistical evidence for an influence on the incentive properties of the market mechanism. This is an encouraging result as theory predicts heuristics to ruin the mechanism’s incentive properties. Copyright © 2015 John Wiley & Sons, Ltd

    Developing Optimization Techniques for Logistical Tendering Using Reverse Combinatorial Auctions

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    In business-to-business logistical sourcing events, companies regularly use a bidding process known as tendering in the procurement of transportation services from third-party providers. Usually in the form of an auction involving a single buyer and one or more sellers, the buyer must make decisions regarding with which suppliers to partner and how to distribute the transportation lanes and volume among its suppliers; this is equivalent to solving the optimization problem commonly referred to as the Winner Determination Problem. In order to take into account the complexities inherent to the procurement problem, such as considering a supplier’s network, economies of scope, and the inclusion of business rules and preferences on the behalf of the buyer, we present the development of a mixed-integer linear program to model the reverse combinatorial auction for logistical tenders

    Theoretical and Computational Basis for Economical Ressource Allocation in Application Layer Networks - Annual Report Year 1

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    This paper identifies and defines suitable market mechanisms for Application Layer Networks (ALNs). On basis of the structured Market Engineering process, the work comprises the identification of requirements which adequate market mechanisms for ALNs have to fulfill. Subsequently, two mechanisms for each, the centralized and the decentralized case are described in this document. --Grid Computing

    Iterative Combinatorial Auction for Carrier Collaboration in Logistic Services

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    In collaborative logistics, multiple carriers form a network to share their transportation capacities. Collaboration among carriers results in improved resource utilization and, therefore, reduced costs. In this thesis, we propose an auction-based model for carrier collaboration in transportation services. The model achieves carrier collaboration through facilitating the negotiation among carriers over a group of shipping orders required by one or a group of shippers. The negotiation is conducted through a combinatorial iterative auction mechanism with the objective of minimizing the carriers’ overall costs. We first present a centralized carrier collaboration problem model in which a central entity has all required information to compute an optimal solution. We then consider a more realistic game theoretic setting where auction-based mechanism is applied to deal with self-interests of carriers. Compared with one-shot auctions, the proposed iterative bidding framework has the properties of reducing carriers’ information revelation and accommodating dynamic changes during the bidding process. Experimental results show that the procurement cost performance and the quality of solutions computed using the proposed iterative auction model is close to that of the optimal solutions
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