Maximizing the value of resources and producing less waste are strategic decisions affecting sustainability and competitive advantage. Sustainable closed-loop supply chains (CLSCs) are designed to minimize waste by circling back (repairing, reselling, or dismantling for parts) previously discarded products into the value chain. This study presents a novel two-stage fuzzy supplier selection and order allocation model in a CLSC. In Stage 1, we use the fuzzy best-worst method (BWM) to select the most suitable suppliers according to economic, environmental, social, and circular criteria. In Stage 2, we use a multi-objective mixed-integer linear programming (MOMILP) model to design a multi-product, multi-period, CLSC network, and inventory-location-routing, vehicle scheduling , and quantity discounts considerations. In the proposed MOMILP , the total network costs, the undesired environmental effects , and the lost sales are minimized while job opportunities and sustainable supplier purchases are maximized. A fuzzy goal programming approach is proposed to transform the MOMILP into a single objective model. We present a case study to demonstrate the applicability of the proposed method in the garment manufacturing and distribution industry.