Recently, we have seen an increasing use of customer choice behavior models in revenue management problems. This growing interest is mainly because of dissatisfactions with the limitations of traditional revenue management models. Modeling customer behavior, followed by revenue optimization techniques which are used to deal with such complex models, are main steps in taking advantage of these studies.;However, as a column generation algorithm is considered to solve CDLP on real-size network, we face a linear fractional programming subproblem which is NP-hard. We provide a simple heuristic approach to tackle this complexity. According to our numerical results, the heuristic, both in the terms of quality of the obtained solution and processing time, performs better than present approaches.;In this research, we consider the choice-based, deterministic, linear programming (CDLP) model of Gallego et al. [20] and further works done by Van Ryzin and Liu [40] and Vulcano [9] in which customers belong to overlapping segments. The prices are fixed and a firm wants to maximize its revenue by deciding the optimal assortment of products to offer.
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