Hybridization of improved binary bat algorithm for optimizing targeted offers problem in direct marketing campaigns

Abstract

One of the biggest business problems of marketers, is to optimize the return on investments of direct Marketing campaign. This main purpose which can only be ensured by targeting the appropriate customer. The main challenge faced by companies when advertising, is to configure properly a campaign, by choosing the right target, so A high user acceptance rate is ensured to advertisements. However, when dealing with an important size of data, the important specification to consider is the combinatorial aspect of the problem and the limitation of the approach based on mathematical programming methods. In this work, and considering the optimization of targeting offers as an of NP-hard problems, we concluded that the use of a meta heuristic algorithm is more suitable to use a classical (exact) method. We choice to use an improved bat Algorithm hybridized with Genetic Algorithm. The results of computational experiments confirmed that the proposed algorithm gives competitive results.