An Optimal Mechanism for Sponsored Search Auctions on the Web and Comparison With Other Mechanisms

In this paper, we first describe a framework to model the sponsored search auction on the web as a mechanism design problem. Using this framework, we describe two well-known mechanisms for sponsored search auction-Generalized Second Price (GSP) and Vickrey-Clarke-Groves (VCG). We then derive a new mechanism for sponsored search auction which we call optimal (OPT) mechanism. The OPT mechanism maximizes the search engine's expected revenue, while achieving Bayesian incentive compatibility and individual rationality of the advertisers. We then undertake a detailed comparative study of the mechanisms GSP, VCG, and OPT. We compute and compare the expected revenue earned by the search engine under the three mechanisms when the advertisers are symmetric and some special conditions are satisfied. We also compare the three mechanisms in terms of incentive compatibility, individual rationality, and computational complexity. Note to Practitioners-The advertiser-supported web site is one of the successful business models in the emerging web landscape. When an Internet user enters a keyword (i.e., a search phrase) into a search engine, the user gets back a page with results, containing the links most relevant to the query and also sponsored links, (also called paid advertisement links). When a sponsored link is clicked, the user is directed to the corresponding advertiser's web page. The advertiser pays the search engine in some appropriate manner for sending the user to its web page. Against every search performed by any user on any keyword, the search engine faces the problem of matching a set of advertisers to the sponsored slots. In addition, the search engine also needs to decide on a price to be charged to each advertiser. Due to increasing demands for Internet advertising space, most search engines currently use auction mechanisms for this purpose. These are called sponsored search auctions. A significant percentage of the revenue of Internet giants such as Google, Yahoo!, MSN, etc., comes from sponsored search auctions. In this paper, we study two auction mechanisms, GSP and VCG, which are quite popular in the sponsored auction context, and pursue the objective of designing a mechanism that is superior to these two mechanisms. In particular, we propose a new mechanism which we call the OPT mechanism. This mechanism maximizes the search engine's expected revenue subject to achieving Bayesian incentive compatibility and individual rationality. Bayesian incentive compatibility guarantees that it is optimal for each advertiser to bid his/her true value provided that all other agents also bid their respective true values. Individual rationality ensures that the agents participate voluntarily in the auction since they are assured of gaining a non-negative payoff by doing so.

On trade-off solution pairs in a special type of transportation problem

Abstract is not available.

Enhancing 'Mobility' through Integrated Transportation and Traffic Management

During the course of preparation of a master plan for the transportation networks in Bangalore city, mapping the various initiatives and interventions planned towards addressing mobility, existing situation and implications of some of the proposed interventions was analysed. The inferences are based on existing transportation network; synthesis of various transportation related studies and proposed infrastructure initiatives (road works) in Bangalore. Broadly, they can be summarized as following five aspects: I. Need for ~Sreclassifying~T existing road networks (arterial and sub-arterial) with effective geospatial database in the back-end. II. The proposed Core Ring Road at surface grade may not be feasible. III. Current interventions encouraging more independent motorable transport by way of road widening, construction of underpasses, flyovers and grade-separators would not ease traffic congestion when addressed in isolation. IV. Factors affecting time and cost-overruns in infrastructure projects and ways to tackle are discussed. V. Initiatives required for addressing effective planning for operations recommended.

On Sharma-Swarup algorithm for time minimising transportation problems

In this note, the fallacy in the method given by Sharma and Swarup, in their paper on time minimising transportation problem, to determine the setS hkof all nonbasic cells which when introduced into the basis, either would eliminate a given basic cell (h, k) from the basis or reduce the amountx hkis pointed out.

Design of an optimal auction for sponsored search auctions

In this paper we first describe a framework to model the sponsored search auction on the web as a mechanism design problem. Using this framework, we design a novel auction which we call the OPT (optimal) auction. The OPT mechanism maximizes the search engine's expected revenue while achieving Bayesian incentive compatibility and individual rationality of the advertisers. We show that the OPT mechanism is superior to two of the most commonly used mechanisms for sponsored search namely (1) GSP (Generalized Second Price) and (2) VCG (Vickrey-Clarke-Groves). We then show an important revenue equivalence result that the expected revenue earned by the search engine is the same for all the three mechanisms provided the advertisers are symmetric and the number of sponsored slots is strictly less than the number of advertisers.

Optical trapping and transportation of carbon nanotubes made easy by decorating with palladium

Individual carbon nanotubes being substantially smaller than the wavelength of light, are not much responsive to optical manipulation. Here we demonstrate how decorating single-walled carbon nanotubes with palladium particles makes optical trapping and manipulation easier. Palladium decorated nanotubes (Pd/SWNTs) have higher effective dielectric constant and are trapped at much lower laser power level with greater ease. In addition, we report the transportation of Pd/SWNTs using an asymmetric line trap. Using this method carbon nanotubes can be transported in any desired direction with high transportation speed. (c) 2006 Optical Society of America.

Potential of bio-DME as a transportation fuel for India

This article discusses the potential of bio-dimethyl ether (DME) as a promising fuel for India in the transportation sector where a majority of imported petroleum in the form of diesel is used. Specifically, the suitability of DME in terms of its properties vis-a-vis those of diesel, ability to liquefy DME at low pressures similar to liquefied petroleum gas (LPG), and ease of production from renewable feedstock (biomass), and most importantly, very low emissions including near-zero soot levels are some of the features that make it an attractive option. A detailed review presents the state-of-the-art on various aspects such as estimates of potential bio-DME production, methods of synthesis of bio-DME, important physicochemical properties, fuel-injection system-related concerns (both conventional and common-rail system), fuel spray characteristics which have a direct bearing on the engine performance, and finally, exhaust emissions. Future research directions covering all aspects from production to utilization are summarized (C) 2010 American Institute of Physics. doi:10.1063/1.3489529]

Achieving sustainable transportation system for Indian cities - problems and issues

This article aims at identifying the research issues and challenges that need to be addressed to achieve sustainable transportation system for Indian cities. The same is achieved by understanding the current system and trends of urbanization, motorization and modal shares in India; and their impact on mobility and safety (the two basic goals of transportation) as well as environment. Further, the article explores the efforts by the central and state governments in India to address the sustainability issues, and the problems and issues over and above the present efforts to achieve sustainability. The article concludes by summarizing the research issues with respect to planning/modelling, non-motorized transport, public transport, driver behaviour and road safety and traffic management. It is expected that these research issues will provide potential directions for carrying out further research aimed at achieving sustainable transport system for Indian cities.

Multi-Armed Bandit Mechanisms for Multi-Slot Sponsored Searth Auctions

In pay-per click sponsored search auctions which are currently extensively used by search engines, the auction for a keyword involves a certain number of advertisers (say k) competing for available slots (say m) to display their ads. This auction is typically conducted for a number of rounds (say T). There are click probabilities mu_ij associated with agent-slot pairs. The search engine's goal is to maximize social welfare, for example, the sum of values of the advertisers. The search engine does not know the true value of an advertiser for a click to her ad and also does not know the click probabilities mu_ij s. A key problem for the search engine therefore is to learn these during the T rounds of the auction and also to ensure that the auction mechanism is truthful. Mechanisms for addressing such learning and incentives issues have recently been introduced and would be referred to as multi-armed-bandit (MAB) mechanisms. When m = 1,characterizations for truthful MAB mechanisms are available in the literature and it has been shown that the regret for such mechanisms will be O(T^{2/3}). In this paper, we seek to derive a characterization in the realistic but nontrivial general case when m > 1 and obtain several interesting results.

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.

Bidding Dynamics of Rational Advertisers in Sponsored Search Auctions on the Web

In this paper, we address a key problem faced by advertisers in sponsored search auctions on the web: how much to bid, given the bids of the other advertisers, so as to maximize individual payoffs? Assuming the generalized second price auction as the auction mechanism, we formulate this problem in the framework of an infinite horizon alternative-move game of advertiser bidding behavior. For a sponsored search auction involving two advertisers, we characterize all the pure strategy and mixed strategy Nash equilibria. We also prove that the bid prices will lead to a Nash equilibrium, if the advertisers follow a myopic best response bidding strategy. Following this, we investigate the bidding behavior of the advertisers if they use Q-learning. We discover empirically an interesting trend that the Q-values converge even if both the advertisers learn simultaneously.

Truthful multi-armed bandit mechanisms for multi-slot sponsored search auctions

In pay-per-click sponsored search auctions which are currently extensively used by search engines, the auction for a keyword involves a certain number of advertisers (say k) competing for available slots (say m) to display their advertisements (ads for short). A sponsored search auction for a keyword is typically conducted for a number of rounds (say T). There are click probabilities mu(ij) associated with each agent slot pair (agent i and slot j). The search engine would like to maximize the social welfare of the advertisers, that is, the sum of values of the advertisers for the keyword. However, the search engine does not know the true values advertisers have for a click to their respective advertisements and also does not know the click probabilities. A key problem for the search engine therefore is to learn these click probabilities during the initial rounds of the auction and also to ensure that the auction mechanism is truthful. Mechanisms for addressing such learning and incentives issues have recently been introduced. These mechanisms, due to their connection to the multi-armed bandit problem, are aptly referred to as multi-armed bandit (MAB) mechanisms. When m = 1, exact characterizations for truthful MAB mechanisms are available in the literature. Recent work has focused on the more realistic but non-trivial general case when m > 1 and a few promising results have started appearing. In this article, we consider this general case when m > 1 and prove several interesting results. Our contributions include: (1) When, mu(ij)s are unconstrained, we prove that any truthful mechanism must satisfy strong pointwise monotonicity and show that the regret will be Theta T7) for such mechanisms. (2) When the clicks on the ads follow a certain click precedence property, we show that weak pointwise monotonicity is necessary for MAB mechanisms to be truthful. (3) If the search engine has a certain coarse pre-estimate of mu(ij) values and wishes to update them during the course of the T rounds, we show that weak pointwise monotonicity and type-I separatedness are necessary while weak pointwise monotonicity and type-II separatedness are sufficient conditions for the MAB mechanisms to be truthful. (4) If the click probabilities are separable into agent-specific and slot-specific terms, we provide a characterization of MAB mechanisms that are truthful in expectation.

Biomass to liquid transportation fuel via Fischer Tropsch synthesis - Technology review and current scenario

Current global energy scenario and the environmental deterioration aspect motivates substituting fossil fuel with a renewable energy resource - especially transport fuel. This paper reviews the current status of trending biomass to liquid (BTL) conversion processes and focuses on the technological developments in Fischer Tropsch (FT) process. FT catalysts in use, and recent understanding of FT kinetics are explored. Liquid fuels produced via FT process from biomass derived syngas promises an attractive, clean, carbon neutral and sustainable energy source for the transportation sector. Performance of the FT process with various catalysts, operating conditions and its influence on the FT products are also presented. Experience from large scale commercial installations of FT plants, primarily utilizing coal based gasifiers, are discussed. Though biomass gasification plants exist for power generation via gas engines with power output of about 2 MWe; there are only a few equivalent sized FT plants for biomass derived syngas. This paper discusses the recent developments in conversion of biomass to liquid (BTL) transportation fuels via FT reaction and worldwide attempts to commercialize this process. All the data presented and analysed here have been consolidated from research experiences at laboratory scale as well as from industrial systems. Economic aspects of BTL are reviewed and compared. (C) 2015 Elsevier Ltd. All rights reserved.