Generic Pareto local search metaheuristic for optimization of targeted offers in a bi-objective direct marketing campaign

Abstract

International audienceCross-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

Challenges for Connecting Citizens and Smart Cities: ICT, E-Governance and Blockchain

“…In this case, the system could consider individuals' preferences and the current wishes of those accessing the platform. This direct marketing problem [66] should present suitable offers for each person, promoting the local communities [67], increasing cities' income and social welfare and urban cleaning, among other things.…”

A matheuristic for a customer assignment problem in direct marketing

“…These two-step heuristics are competitive with the best heuristics of Nobibon et al (2011) . Finally, Coelho et al (2017) develop a metaheuristic for a variant of the planning problem considered by Nobibon et al (2011) where the objective function includes a reward-to-variability indicator, which is inspired by the Sharpe ratio. One major difference between our planning problem (cf.…”

GATeS: A Hybrid Algorithm Based on Genetic Algorithm and Tabu Search for the Direct Marketing Problem

“…Later [22] has adapted a mathematical model to solve almost all instances generated so far, including cannibalism. Coelho et al [23] extended the VNS proposed by [17], to a bi-objective version of the problem based on the concepts of maximizing profits and, at the same time, searching for a set of customers with less variability over their expected return.…”