A Nash Bargaining Approach to Retention Enhancing Bid Optimization in Sponsored Search Auctions with Discrete Bids

Bid optimization is now becoming quite popular in sponsored search auctions on the Web. Given a keyword and the maximum willingness to pay of each advertiser interested in the keyword, the bid optimizer generates a profile of bids for the advertisers with the objective of maximizing customer retention without compromising the revenue of the search engine. In this paper, we present a bid optimization algorithm that is based on a Nash bargaining model where the first player is the search engine and the second player is a virtual agent representing all the bidders. We make the realistic assumption that each bidder specifies a maximum willingness to pay values and a discrete, finite set of bid values. We show that the Nash bargaining solution for this problem always lies on a certain edge of the convex hull such that one end point of the edge is the vector of maximum willingness to pay of all the bidders. We show that the other endpoint of this edge can be computed as a solution of a linear programming problem. We also show how the solution can be transformed to a bid profile of the advertisers.

Accurate Parameter Estimation of Contaminant Transport Inverse Problem using Paartaicle Swarm Optimization

Swarm Intelligence techniques such as particle swarm optimization (PSO) are shown to be incompetent for an accurate estimation of global solutions in several engineering applications. This problem is more severe in case of inverse optimization problems where fitness calculations are computationally expensive. In this work, a novel strategy is introduced to alleviate this problem. The proposed inverse model based on modified particle swarm optimization algorithm is applied for a contaminant transport inverse model. The inverse models based on standard-PSO and proposed-PSO are validated to estimate the accuracy of the models. The proposed model is shown to be out performing the standard one in terms of accuracy in parameter estimation. The preliminary results obtained using the proposed model is presented in this work.

Halogen Bonding and Structural Modularity in 2,3,4-and 3,4,5-Trichlorophenol

The crystal structure of 3,4,5-trichlorophenol contains hydrogen bonded domains that occur respectively in the structures of 4-chlorophenol and 3,5-dichlorophenol. Such modularity is also seen in 2,3,4-trichlorophenol. These structures, and those of the six isomeric dichlorophenols, illustrate the importance of halogen bonding as a structure determining interaction.

Structural Variability in the Monofluoroethynylbenzenes Mediated through Interactions Involving ``Organic'' Fluorine

Competition among weak intermolecular interactions can lead to polymorphism, the appearance of various crystalline forms of a substance with comparable cohesive energies. The crystal structures of 2-fluorophenylacetylene (2FPA) and 3-fluorophenylacetylene (3FPA), both of which are liquids at ambient conditions, have been determined by in situ cryocrystallization. Both compounds exhibit dimorphs, with one of the forms observed in common, P2(1), Z = 2 and the other form being Pna2(1), Z = 4 for 2FPA and P2(1)/c, Z = 12 for 3FPA. Variations in the crystal structures of the dimorphs of each of these compounds arise from subtle differences in the way in which weak intermolecular interactions such as C-H center dot center dot center dot pi and C-H center dot center dot center dot F are manifested. The interactions involving ``organic'' fluorine, are entirely different from those in the known structure of 4-fluorophenylacetylene (4FPA), space group P2(1)/c, Z = 4. The commonalities and differences in these polymorphs of 2FPA and 3FPA have been analyzed in terms of supramolecular synthons and extended long-range synthon aufbau module (LSAM) patterns. These structures are compared with the three polymorphs of phenylacetylene, in terms of the T-shaped C-H center dot center dot center dot pi interaction, a feature common to all these structures.

Robust Aeroelastic Optimization Of Composite Helicopter Rotor

A robust aeroelastic optimization is performed to minimize helicopter vibration with uncertainties in the design variables. Polynomial response surfaces and space-¯lling experimental designs are used to generate the surrogate model of aeroelastic analysis code. Aeroelastic simulations are performed at the sample inputs generated by Latin hypercube sampling. The response values which does not satisfy the frequency constraints are eliminated from the data for model ¯tting. This step increased the accuracy of response surface models in the feasible design space. It is found that the response surface models are able to capture the robust optimal regions of design space. The optimal designs show a reduction of 10 percent in the objective function comprising six vibratory hub loads and 1.5 to 80 percent reduction for the individual vibratory forces and moments. This study demonstrates that the second-order response surface models with space ¯lling-designs can be a favorable choice for computationally intensive robust aeroelastic optimization.