Please use this identifier to cite or link to this item: http://www.repositorio.ufop.br/handle/123456789/5466
Title: A hybrid variable neighborhood search algorithm for targeted offers in direct marketing.
Authors: Oliveira, Thays Aparecida de
Coelho, Vitor Nazário
Souza, Marcone Jamilson Freitas
Boava, Diego Luiz Teixeira
Boava, Fernanda Maria Felício Macêdo
Coelho, Igor Machado
Coelho, Bruno Nazário
Keywords: Direct marketing
Targeted offers problem
General variable neighborhood search
Operational research
Issue Date: 2015
Citation: OLIVEIRA, T. A. de et al. A hybrid variable neighborhood search algorithm for targeted offers in direct marketing. Electronic Notes in Discrete Mathematics, v. 47, p. 205-212, 2015. Disponível em: <http://www.sciencedirect.com/science/article/pii/S1571065314000699>. Acesso em: 24 mar. 2015.
Abstract: This paper focuses on the targeted offers problem in direct marketing campaigns. The main objective is to maximize the feedback of customers purchases, offering products for the set of customers with the highest probability of positively accepting the offer and, at the same time, minimizing the operational costs of the campaign. Given the combinatorial nature of the problem and the large volume of data, involving instances with up to one million customers, approaches solely based on mathematical programming methods, said exact, appear limited and infeasible. In this paper, the use of a hybrid heuristic algorithm, based on the Greedy Randomized Adaptive Search Procedures and General Variable Neighborhood Search, is proposed. Computational experiments performed on a set of test problems from the literature show that the proposed algorithm was able to produce competitive solutions.
URI: http://www.repositorio.ufop.br/handle/123456789/5466
metadata.dc.identifier.doi: https://doi.org/10.1016/j.endm.2014.11.027
ISSN: 1571-0653
metadata.dc.rights.license: O periódico Electronic Notes in Discrete Mathematics concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3598750832435.
Appears in Collections:DECAD- Artigos publicados em periódicos

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