This paper considers the capacity determination in a closed-loop supply chain network when a queueing system is established in the reverse flow. Since the queueing system imposes costs on the model, the decision maker faces the challenge of determining the capacity of facilities in such a way that a compromise between the queueing costs and the fixed costs of opening new facilities could be obtained. We develop a De Novo programming approach to determine the capacity of recovery facilities in the reverse flow. To this aim, a mixed integer nonlinear programming (MINLP) model is integrated with the De Novo programming and the robust counterpart of this model is proposed to cope with the uncertainty of the parameters. To solve the model, an interactive fuzzy programming approach is combined with the hard worst case robust programming. Numerical results show the performance of the developed model in determining the capacity of facilities.

International trades rely on robust supply chains. However, supply chains are vulnerable to disruptions. Before implementing lean construction, identifying construction supply chain vulnerabilities (CSCV) is crucial to avoid failure. Meanwhile, an unfavorable macro-environmental context (e.g., challenging economic and political situations) can potentially affect the behavior of CSCV. This paper aims to identify and prioritize CSCV under an unfavorable macro-environmental context in a real-world case and then analyze the changes in CSCV in a period coinciding with the Covid-19 outbreak. A literature review led us to extract 26 variables that were then prioritized using the responses from questionnaires distributed among 72 participants in the studied country. A descriptive statistical approach was used to analyze the results, which showed that unlike the normal contexts mentioned in previous studies, under an unfavorable context, such CSCV as "price and exchange rate fluctuations", "supply-demand volatility", "financial issues", and "political challenges" gained priority. Moreover, analyzing the changes in CSCV indicated that the studied construction supply chain has become more vulnerable in the mentioned period. Considering the identified CSCV, this paper suggests that managers focus more on tools such as the Last Planner System and value stream mapping when implementing lean.