Dentistry

Supply chain network design entails strategic decisions that critically shape the operational framework of a supply chain. The purpose of this study is to develop and optimize a green dental tourism supply chain network using metaheuristic algorithms. This applied research combines field surveys and library-based methods for data collection. Empirical data were obtained from dental clinics and three- and four-star hotels in Qom Province, forming the basis for model implementation. The proposed network integrates environmental considerations and seeks to minimize total supply chain cost. A multi-objective optimization model is formulated and solved using two algorithms: NRGA (Non‑dominated Ranked Genetic Algorithm) and NSGA‑II (Non‑dominated Sorting Genetic Algorithm II). The comparative analysis demonstrates that NSGA‑II achieves more efficient solutions and superior ranking of Pareto‑optimal fronts across the model’s multiple objectives. This study advances the design and optimization of sustainable dental tourism supply chains, providing practical insights for policymakers and industry stakeholders aiming to promote environmentally responsible and economically viable tourism services.