A robust possibilistic programming model for a responsive closed loop supply chain network design

Concerns about the outbreak of perturbations and their major losses have led a lot of researchers to consider reliability while designing supply chain networks. In addition, the inherent uncertainty of input parameters is another important issue in the design of supply chain networks due to its adverse effects on strategic, tactical, and operational decisions. This present paper proposes a new model for designing a sustainable closed-loop single-product multi-component multi-level logistics network under uncertainty conditions. The model is based on a robust possibilistic programming approach. The proposed models not only minimize the total costs but also develop an effective resistant network under disruptions strikes and control the product delivery speed at appropriate safety levels. Finally, the effectiveness and applicability of the model are displayed in a national project with the actual nominal data.