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Real-Time Bidding (RTB) is an important paradigm in display advertising,where advertisers utilize extended information and algorithms served by DemandSide Platforms (DSPs) to improve advertising performance. A common problem forDSPs is to help advertisers gain as much value as possible with budgetconstraints. However, advertisers would routinely add certain key performanceindicator (KPI) constraints that the advertising campaign must meet due topractical reasons. In this paper, we study the common case where advertisersaim to maximize the quantity of conversions, and set cost-per-click (CPC) as aKPI constraint. We convert such a problem into a linear programming problem andleverage the primal-dual method to derive the optimal bidding strategy. Toaddress the applicability issue, we propose a feedback control-based solutionand devise the multivariable control system. The empirical study based onreal-word data from Taobao.com verifies the effectiveness and superiority ofour approach compared with the state of the art in the industry practices.

Bid Optimization by Multivariable Control in Display Advertising