Topic
Bidding
About: Bidding is a research topic. Over the lifetime, 15371 publications have been published within this topic receiving 294233 citations. The topic is also known as: competitive bidding.
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TL;DR: In this article, a stochastic programming model that integrates strategic bids or offers for electricity (in quantities and prices) in a deregulated electricity market is introduced to maximize the profits of a producer of electricity who manages a series of power plants along a river.
Abstract: This paper introduces a stochastic programming model that integrates strategic bids or offers for electricity (in quantities and prices) in a deregulated electricity market. The model is designed to maximize the profits of a producer of electricity who manages a series of power plants along a river. The model is compared with a previously reported stochastic model where the bidding process is disregarded. The superiority of the new model is empirically demonstrated on historical data.
72 citations
01 May 1997
TL;DR: A novel approach for dynamically creating and managing agent communities or virtual clusters that use Contract Net bidding for multi-agent negotiation and Mediator agents to co-ordinate their actions.
Abstract: Manufacturing industries are facing increasing competitive challenges in both maintaining their existing markets and improving their capability to respond efficiently to marketplace needs. New architectures are required for next generation of manufacturing systems which must be developed to meet these challenges. This paper introduces a novel approach for dynamically creating and managing agent communities or virtual clusters. These virtual clusters use Contract Net bidding for multi-agent negotiation and Mediator agents to co-ordinate their actions. The manufacturing system is thus populated by heterogeneous agents and structures of control which operate autonomously during the planning and execution periods of the manufacturing tasks.
72 citations
TL;DR: It is proved that there exist bidding and charging strategies that maximize social welfare and it is proposed a decentralized realization of the double-sided auction with lightweight network feedback and a pricing method which does not need a charging infrastructure.
Abstract: Auction mechanisms are used for allocating a resource among multiple agents with the objective to maximize social welfare. What makes auctions attractive is that they are agnostic to utility functions of agents. Auctions involve a bidding method by agents-buyers, which is then mapped by a central controller to an allocation and a payment for each agent. In autonomic networks comprising self-interested nodes with different needs and utility functions, each entity possesses some resource and can engage in transactions with others to achieve its needs. In fact, efficient network operation relies on node synergy and multi-lateral resource trading. Nodes face the dilemma of devoting their limited resource to their own benefit versus acting altruistically and anticipating to be aided in the future. Wireless ad-hoc networks, peer-to-peer networks and disruption-tolerant networks are instances of autonomic networks where the challenges above arise and the traded resource is energy, bandwidth and storage space respectively. Clearly, the decentralized complex node interactions and the double node role as resource provider and consumer amidst resource constraints cannot be addressed by single-sided auctions and even more by mechanisms with a central controller. We introduce a double-sided auction market framework to address the challenges above. Each node announces one bid for buying and one for selling the resource. We prove that there exist bidding and charging strategies that maximize social welfare and we explicitly compute them. We generalize our result to a generic network objective. Nodes are induced to follow these strategies, otherwise they are isolated by the network. Furthermore, we propose a decentralized realization of the double-sided auction with lightweight network feedback. Finally, we introduce a pricing method which does not need a charging infrastructure. Simulation results verify the desirable properties of our approach.
72 citations
04 Jan 2009
TL;DR: The main result is an online mechanism for allocation and pricing in this model with many desirable game-theoretic properties, which bounds the earnings of speculators who are in the game to obtain the cancellation fees.
Abstract: Many advertisers (bidders) use Internet systems to buy display advertisements on publishers' webpages or on traditional media such as radio, TV and newsprint. They seek a simple, online mechanism to reserve ad slots in advance. On the other hand, media publishers (sellers) represent a vast and varying inventory, and they too seek automatic, online mechanisms for pricing and allocating such reservations.We propose and study a simple model for auctioning such ad slot reservations in advance. A seller will display a set of slots at some point T in the future. Until T, bidders arrive sequentially and place a bid on the slots they are interested in. The seller must decide immediately whether or not to grant a reservation. Our model allows the seller to cancel at any time any reservation made earlier, in which case the holder of the reservation incurs a utility loss amounting to a fraction of her value for the reservation and may also receive a cancellation fee from the seller.Our main result is an online mechanism for allocation and pricing in this model with many desirable game-theoretic properties. It is individually rational. Winners have an incentive to be honest and bidding one's true value dominates any lower bid. Further, it bounds the earnings of speculators who are in the game to obtain the cancellation fees. The mechanism in addition has optimization guarantees. Its revenue is within a constant fraction of the a posteriori revenue of the Vickrey-Clarke-Groves (VCG) mechanism which is known to be truthful (in the offline case). Our mechanism's efficiency is within a constant fraction of the a posteriori optimally efficient solution. If efficiency also takes into account the utility losses of bidders whose reservation was canceled, we show that our mechanism matches (for appropriate values of the parameters) an upper bound on the competitive ratio of any deterministic online algorithm.Our mechanism's technical core is a variant of the online weighted bipartite matching problem where unlike prior variants in which one randomizes edge arrivals or bounds edge weights, we may revoke previously committed edges.Our results make no assumptions about bidders' arrival order or value distribution. They still hold if we replace items with elements of a matroid and matchings with independent sets, or if all bidders have additive value for a set of items.
72 citations
Posted Content•
TL;DR: In this article, the authors studied bidding behavior in the auction of radio spectrum for third generation mobile telephone services which took place in the UK in the Spring of 2000 and concluded that several companies' bidding behaviour deviates strongly from straightforward bidding with private values.
Abstract: This article studies bidding behaviour in the auction of radio spectrum for third generation mobile telephone services which took place in the UK in the Spring of 2000. We show that several companies' bidding behaviour deviates strongly from straightforward bidding with private values. In particular some companies' evaluation of the added advantage of having a large licence rather than a small licence seemed to change dramatically during the auction. No compelling explanation of this phenomenon seems available at this stage. We conclude that it is less well understood than previously believed how spectrum auctions work.
71 citations