Honey bee behavior: A multi-agent approach for multiple campaigns assignment problem

This paper address a multi-agent approach using the behavior of honey bee to find out an optimal customer-campaign relationship under certain restrictions for the problem of multiple campaigns assignment. This NP-hard problem is one of the key issues in marketing when producing the optimal campaign. In personalized marketing it is very important to optimize the customer satisfaction and targeting efficiency. Using the behavior of honey bee a multi-agent approach is proposed to overcome the multiple recommendations problem that occur when several personalized campaigns conducting simultaneously. We measure the effectiveness of the propose method with two other methods known as RANDOM and INDEPENDENT using an artificially created customer-campaign preference matrix. Further a generalized Gaussian response suppression function is introduced and it differs among customer classes. An extensive simulation studies are carried out varying on the small to large scale of the customer-campaign assignment matrix and the percentage of recommendations. Computational result of the proposed method shows a clear edge vis-a-vis RANDOM and INDEPENDENT.