this paper represents a complete survey on generation companies’ (gencos’) optimal bidding strategy problem in restructured power markets. in this regard after an introduction to competitive electricity markets, concept of optimal bidding strategy is presented. considering large amount of works accomplished in this area a novel classification is implemented in order to categorize the existing d...

Online auctions have become a popular and effective tool for Internet-based E-markets. We investigate problems and models of optimal adaptive automated bidding in an environment of concurrent online auctions, where multiple auctions for identical items are running simultaneously. We develop new models for a firm where its item valuation derives from the sale of the acquired items via their dema...

Real-time bidding has become one of the largest online advertising markets in the world. Today the bid price per ad impression is typically decided by the expected value of how it can lead to a desired action event to the advertiser. However, this industry standard approach to decide the bid price does not consider the actual effect of the ad shown to the user, which should be measured based on...

This paper proposes a framework for demand estimation with data on bids, bidders’ identities, and auction covariates from a sequence of eBay auctions. First the aspect of bidding in a marketplace environment is developed. Form the simple dynamic auction model with IPV and private bidding costs it follows that if participation is optimal the bidder searches with a ”reservation bid” for low-price...

In this paper we propose a simple tensor-based approach to temporal features modeling that is applicable as means for logistic regression (LR) enhancement. We evaluate experimentally the performance of an LR system based on the proposed model in the ClickThrough Rate (CTR) estimation scenario involving processing of very large multi-attribute data streams. We compare our approach to the existin...

Mobile marketing campaigns qre now largely deployed through the intermediaries of demand side platforms (DSPI) who provide a petformanceintensive real-time bidding (RTB) versian of predictive analytics as a service. Performance thresholds are roughly l00ms for DSPs to decide whether and how much to bidfor a potential client to receive a particular advertisement via their mobile dwice. This deci...

Air-conditioning loads (ACLs) are among the most promising demand side resources for their thermal storage capacity and fast response potential. This paper adopts the principle of market-based control (MBC) for the ACLs to participate in the ancillary services. The MBC method is suitable for the control of distributed ACLs because it can satisfy diversified requirements, reduce the communicatio...

This work is concerned with the application of game-theoretic principles to model competition between demand response aggregators for selling excess energy stored in electrochemical storage devices directly to other aggregators in a power market. This market framework is presented as an alternative to the traditional vertically-integrated market structure, which may be better suited for develop...

ABSTRACT In recent years, RTB(Real Time Bidding) becomes a popular online advertisement trading method. During the auction, each DSP(Demand Side Platform) is supposed to evaluate current opportunity and respond with an ad and corresponding bid price. It’s essential for DSP to find an optimal ad selection and bid price determination strategy which maximizes revenue or performance under budget an...