Analysis and Optimization of a Buffet Pricing Strategy in the Telecommunication Industry Using the Particle Swarm Optimization (PSO) Algorithm - Merdikawati, Silvia; Oktaviani, Revina Dwi; Salahuddin, Salahuddin; Khadijah, Afni (Journal of Artificial Intelligence and Software Engineering, 2025)
Flat-rate pricing (buffet pricing) is a common strategy in the global telecommunications industry, yet its adoption in Indonesia remains limited due to regulatory challenges, network capacity constraints, and diverse customer preferences. This study aims to optimize buffet pricing by considering user segmentation and varied service consumption patterns. A metaheuristic approach, specifically Particle Swarm Optimization (PSO), is employed to determine the optimal pricing that maximizes operator profit while maintaining customer satisfaction. A customer demand model is developed using a triangular distribution to reflect the asymmetric variability of usage. Results indicate that heavy users benefit significantly from flat-rate plans, whereas light users are better served by a hybrid pricing scheme. PSO demonstrates superior adaptability and efficiency compared to conventional methods, particularly when parameter tuning accelerates convergence. The study also highlights the importance of pricing flexibility to address heterogeneous customer needs. This study offers practical contributions to the development of data-driven, competitive pricing strategies in the evolving telecommunications market.