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One of the major challenges of the supply chain managers is to select the best suppliers among all possible ones for their business. Although the research on the supplier selection with regards to green, sustainability or resiliency criteria has been contributed by many papers, simultaneous consideration of these criteria in a fuzzy environment is rarely studied. Hence, this study proposes a fuzzy decision framework to investigate the sustainable-resilient supplier selection problem for a real case study of palm oil industry in Malaysia. Firstly, the resilient-based sustainable criteria are localized for the suppliers' performance evaluation in palm oil industry of Malaysia. Accordingly, 30 criteria in three different aspects (i.e. general, sustainable and resilient) are determined by statistical tests. Moreover, a hyper-hybrid model with the use of FDEMATEL (fuzzy decision-making trial and evaluation laboratory), FBWM (fuzzy best worst method), FANP (fuzzy analytical network process) and FIS (fuzzy inference system), simultaneously is developed to employ their merits in an efficient way. In this framework, regarding the outset, the relationships among the criteria/sub-criteria are obtained by FDEMATEL method. Then, initial weights of the criteria/sub-criteria are measured by FBWM method. Next, the final weights of criteria/sub-criteria considering the interrelationships are calculated by FANP. Finally, the performance of the suppliers is evaluated by FIS method. To show the applicability of this hybrid decisionmaking framework, an industrial case of palm oil in Malaysia is presented. The findings indicate the high performance of the proposed framework in this concept and identify the most important criteria including the cost in general aspects, resource consumption as the most crucial sustainable criterion and agility as the most important resilient criterion.

Pharmaceutical supply chain (PSC) is one of the most important healthcare supply chains and the recent pandemic (COVID-19) has completely proved it. Also, the environmental and social impacts of PSCs are undeniable due to the daily entrance of a large amount of pharmaceutical waste into the environment. However, studies on closed-loop PSCs (CLPSC) are rarely considered real-world requirements such as competition among diverse brands of manufacturers, the dependency of customers’ demand on products’ price and quality, and diverse reverse flows of end-of-life medicines. In this study, a scenario-based Multi-Objective Mixed-Integer Linear Programming model is developed to design a sustainable CLPSC, which investigates the reverse flows of expired medicines as three classes (must be disposed of, can be remanufactured and can be recycled). To study the competitive market and deal with demand uncertainty, a novel scenario-based game theory model is proposed. The demand function for each brand depends on the price and quality provided. Then, a hybrid solution approach is provided by combining the LP-metrics method with a heuristic algorithm. Furthermore, a real case study is investigated to evaluate the application of the model. Finally, sensitivity analysis and managerial insights are provided. The numerical results show that the proposed classification of reverse flows leads to proper waste management, making money, and reducing both disposal costs and raw material usage. Moreover, competition increases PSCs performance and improves the supply of products to pharmacies. Supplementary Information The online version contains supplementary material available at 10.1007/s10479-021-03961-0.

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