Abstract
The Product Line Design (PLD) problem is an NP-hard combinatorial optimization problem in marketing that aims at determining an optimal product line through which a firm can optimize a desired objective, like its profits or market share. Since the PLD problem has been proved to have high complexity in real-life applications, high-quality solutions have been detected by researchers who develop various optimization methods and test their performance. The Bees Algorithm (BA) is a successful swarm intelligent optimization algorithm which is based on the behavior of bees. The aim of this research is to develop and assess BA in the optimal PLD problem. In this effort, a set of fuzzy rules has been developed to autonomously compute parameters for each individual solution throughout the optimization process. The performance of two BA variants is compared with those of popular previous approaches, using both real and simulated data of customer preferences. The findings reveal that BA constitutes an enhanced alternative approach for designing optimal product lines.
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