Optimization of a television advertisement scheduling problem by multi-criteria decision making and dispatching rules

To increase brand awareness, there is no doubt that advertisement can pave the path. This is due mainly to its impact on buyers' decisions and is regarded as advertisement effectiveness. The more effective the advertisement, the steeper its revenue increase. Among all the advertising ways, television is enumerated as one of the most eminent ones. This study focuses on the scheduling problem for a television advertisement. This paper presents a scheduling problem considering Multi-Attribute Decision Making (MADM) and multi-objective mathematical models. In the first stage, the effectiveness of different categories of advertisements in multifarious timeslots is obtained using a hybrid MADM method, namely the Best-Worst Method (BWM) and Weighted Aggregated Sum Product Assessment (WASPAS). In the second stage, we use the weights mentioned above as an input for a multi-objective mathematical model to maximize the display effectiveness of advertisements in line by maximizing the total income. In the last step, the advertisement scheduling is scrutinized using several dispatching rules. The validity of the proposed methodology for identifying the best advertisements' planning is discussed using three test problems. The results of all test problems as mentioned above and their comparison with the presented real-life case study show that the proposed methodology highlights an optimal solution.

Automated summary

This study focuses on the scheduling problem for television advertisements using multi-attribute decision making and multi-objective mathematical models. The effectiveness of different categories of advertisements in different timeslots is evaluated using a hybrid MADM method. A multi-objective mathematical model is then used to maximize the display effectiveness of advertisements by maximizing total income. Several dispatching rules are used to examine advertisement scheduling. The proposed methodology is validated using three test problems and shown to provide optimal solutions.