Today, with the development of the Internet, e-commerce and digital advertising, along with traditional advertising, have attracted the attention of many sectors and businesses, including the agricultural industry. One of the most consumed agricultural products is tea, which advertising plays a significant role in attracting more customers and improving the efficiency of its supply chain. Therefore, managing the supply chain of such product should be monitored and configured effectively considering sustainability aspects. The aim of this study is to design a dual-channel Sustainable Closed-Loop Supply Chain (SCLSC) network for tea industry for the first time. Then, a Mixed Integer Linear Programming (MILP) model is proposed for optimizing the total costs, the amount of emissions and the number of created job vacancies. In addition, customer demand is dependent on traditional and digital advertising rates and product prices. For solving this model in small dimensions, LP-metric method and in high dimensions, four meta-heuristic multi-objective algorithms including Simulated Annealing Algorithm (MOSA), Particle Swarm Optimization (MOPSO), Gray Wolf Optimizer (MOGWO) and Whale Optimization Algorithm (MOWOA) were used and their results and performance were compared. Furthermore, sensitivity analysis was performed to further evaluate some parameters such as demand. The obtained results confirmed the validity of the planned model and the correctness of its solution method. Finally, practical insights are provided for the related managers and tea producer countries.