Product family design with supply chain design within the framework of a circular economy adds more complexity to meeting diverse demands. This chapter investigates a product family design problem in a stochastic three-echelon supply chain, including a manufacturer, retailers, and customers under demand uncertainty. Also, two groups of customers are considered that the first seeks cheaper products, and the second seeks higher quality products. So, it is essential to determine the quality level and cost of products so that both groups of customers are satisfied. In this research, both mandatory and arbitrary modules are incorporated into product design, with customers selecting the arbitrary modules. This approach enhances product variety based on customer preferences, minimizes waste from unnecessary materials and components, and supports sustainable production practices and a circular economy. Considering the variety of demands in product family problems, the retailers should be located so that the transportation cost is reduced and the demands are satisfied, simultaneously. In order to increase the efficiency of resources and reduce environmental effects, a limit has been considered for serving customers, in which each customer is only allowed to buy from retailers who are present in the customer’s area. The objective of the proposed model is defined as profit maximization. Also, the costs of the fixed development, transportation, production, and locating of retailers are considered in the model. In addition to locating retailers, allocating them to the markets is considered. Next, we developed a sensitivity analysis and a dimensional analysis for the model, and due to NP-hard construction of the model, a hybrid genetic algorithm and simulated annealing (GASA) is employed. Eventually, the results of the GASA and the exact method are compared, and the GASA’s superiority over the exact method is demonstrated.