Sustainable supply chain network design is a rich area for academic research that is still in its infancy and has potential to affect supply chain performance. Increasing regulations for carbon and waste management are forcing firms to consider their supply chains from ecological and social objectives, but in reality, however, facilities and the links connecting them are disrupted from time to time, due to poor weather, natural or manmade disasters or a combination of any other factors. Supply chain systems drop their sustainability objectives while coping with these unexpected disruptions. Hence, the new challenges for supply chain managers are to design an efficient and effective supply chain network that will be resilient enough to bounce back from any disruption and that also should have sufficient vigilance to offer same sustainability under a disruption state. This paper focuses on ecological sustainability, because an environmental focus in a supply chain system is more important and also links with other pillars of sustainability, as the products need to be produced, packed and transported in an ethical way, which should not harm social balance and the environment. Owing to importance of the considered issue, this paper attempts to introduce a network optimization model for a sustainable and resilient supply chain network by incorporating (1) sustainability via carbon emissions and embodied carbon footprints and (2) resilience by incorporating location-specific risks. The proposed goal programming (GP) model optimizes the total cost, while considering the resilience and sustainability of the supply chain network.

Researchers and practitioners are taking more interest in developing sustainable garment supply chains in recent times. On the other hand, the supply chain manager drops sustainability objectives while coping with unexpected natural and man-made disruption risks. Hence, supply chain managers are now trying to develop sustainable supply chains that are simultaneously resilient enough to cope with disruption risks. Owing to the importance of the considered issue, this study proposed a network optimization model for a sustainable and resilient supply chain network by considering sustainability via embodied carbon footprints and carbon emissions and resilience by considering resilience index. In this paper, initially, a possibilistic fuzzy multi-objective sustainable and resilient supply chain network model is developed for the garment industry considering economic, sustainable, and resilience objectives. Secondly, a possibilistic fuzzy linguistic weight-based interactive solution method is proposed. Finally, a numerical case example is presented to show the applicability of the proposed model and solution methodology.

Modern supply chains are vulnerable to high impact, low probability disruption risks. A supply chain usually operates in such a network of entities where the resilience of one supplier is critical to overall supply chain resilience. Therefore, resilient planning is a key strategic requirement in supplier selection decisions for a competitive supply chain. The aim of this research is to develop quantitative resilient criteria for supplier selection and order allocation in a fuzzy environment. To serve the purpose, a possibilistic fuzzy multi-objective approach was proposed and an interactive fuzzy optimization solution methodology was developed. Using the proposed approach, organizations can tradeoff between cost and resilience in supply networks. The approach is illustrated using a supply chain case from a garments manufacturing company.

Globalisation within supply chains opens many doors for new opportunities but can also result in highly complex, unstable and fragile supply chains. Due to importance of complex network theories in supply chain, the authors examine the advances of complex network theories to understand the properties of these networks in underlying efficient supply chains. In this paper, the resilience metrics for supply chain are developed based on complex network theory. Agent-based simulation approach is used to show the applicability of various complex network models to design the resilient supply chain networks. Simulation results shows that supply chain network can be designed based on complex network theory especially as a scale-free network. It was also concluded that scale-free models have some limitations and cannot accurately represent an efficient and resilient supply chain. Therefore, it is suggested that a scale-free model should be developed that can represent more robust and resilient supply chain networks.

Product recall gains considerable importance in recent times; the reason may be the huge losses faced by manufacturers because of product recall issues. Furthermore, the revenue of the firm is immensely affected as a result of product recall, which may lead to serious outcomes. Huge recall cost (such as repairing or destroying the recalled products and cost of notification) occurs as a result of large recall. Therefore, in order to minimize the quantity and probability of recalls the traceability systems are widely used and considered as a necessary part of product safety strategies. However, from literature it is clear that manufacturers are still struggling to obtain the significant results. This study helps the managers to understand the importance of recall cost by analysing its impact on shareholders profit. Keeping in view the importance of problem, the paper proposed an integrated optimization model to minimize the expected loss to shareholders in recall crisis using batch dispersion methodology. The analysed results show that reduction in traceability level increases the expected shareholders losses while decreasing the operational costs. This will help managers to optimally set the production batch sizes in order to reduce the product recall impact.