Online banner advertisement scheduling for advertising effectiveness

Online banner advertisement, which is the most common form of web advertising, has been catching the eye of online users. It is important for online advertisement publishers to schedule advertisements to maximize advertising effectiveness, which might be a predicted value of click-through-rate. In this paper, a model for online banner advertisement scheduling is presented with a new objective function that includes four factors that influence advertising effectiveness. This paper provides not only the integer programming model with a nonlinear objective function but also two heuristic and meta-heuristic algorithms as solution methodologies. Most importantly, the heuristic approach finds good lower and upper bounds by using the properties of the model. Both randomly generated and standard data sets are used to test the problem. The results indicate the effectiveness and efficiency of these algorithms tested in small and large data sets. In standard data sets, the results show the advertisement specification for which tighter bounds are obtained by using the heuristic approach.