Fairness Driven Slot Allocation Problem in Billboard Advertisement

TL;DR

This paper introduces a fair and efficient algorithm for allocating billboard advertisement slots among advertisers, ensuring maximin fairness and maximizing utility, validated through real-world datasets.

Contribution

It proposes a novel approach to the billboard slot allocation problem that incorporates fairness criteria, specifically maximin fairness, which was not addressed in prior work.

Findings

The approach achieves balanced allocations satisfying maximin fairness.

It maximizes advertisers' utility while maintaining fairness.

Experimental results on real datasets validate effectiveness.

Abstract

In billboard advertisement, a number of digital billboards are owned by an influence provider, and several commercial houses (which we call advertisers) approach the influence provider for a specific number of views of their advertisement content on a payment basis. Though the billboard slot allocation problem has been studied in the literature, this problem still needs to be addressed from a fairness point of view. In this paper, we introduce the Fair Billboard Slot Allocation Problem, where the objective is to allocate a given set of billboard slots among a group of advertisers based on their demands fairly and efficiently. As fairness criteria, we consider the maximin fair share, which ensures that each advertiser will receive a subset of slots that maximizes the minimum share for all the advertisers. We have proposed a solution approach that generates an allocation and provides an approximate maximum fair share. The proposed methodology has been analyzed to understand its time and space requirements and a performance guarantee. It has been implemented with real-world trajectory and billboard datasets, and the results have been reported. The results show that the proposed approach leads to a balanced allocation by satisfying the maximin fairness criteria. At the same time, it maximizes the utility of advertisers.