Generic Pareto local search metaheuristic for optimization of targeted offers in a bi-objective direct marketing campaign.
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2016
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Resumo
Cross-selling campaigns seek to offer the right products to the set of customers with the goal of maximizing
expected profit, while, at the same time, respecting the purchasing constraints set by investors. In this context, a
bi-objective version of this NP-Hard problem is approached in this paper, aiming at maximizing both the
promotion campaign total profit and the risk-adjusted return, which is estimated with the reward-to-variability
ratio known as Sharpe ratio. Given the combinatorial nature of the problem and the large volume of data,
heuristic methods are the most common used techniques. A Greedy Randomized Neighborhood Structure is
also designed, including the characteristics of a neighborhood exploration strategy together with a Greedy
Randomized Constructive technique, which is embedded in a multi-objective local search metaheuristic. The
latter combines the power of neighborhood exploration by using a Pareto Local Search with Variable
Neighborhood Search. Sets of non-dominated solutions obtained by the proposed method are described and
analyzed for a number of problem instances.
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Direct marketing campaign, Sharpe ratio, Cross-selling, Metaheuristics
Citação
COELHO, V. N. et al. Generic Pareto local search metaheuristic for optimization of targeted offers in a bi-objective direct marketing campaign. Computers & Operations Research, v. 78, p. 578-587, 2016. Disponível em: <https://www.sciencedirect.com/science/article/pii/S0305054816302283>. Acesso em: 16 jan. 2018.