Green inventory management in a multi-product, multi-vendor post-disaster construction supply chain

In the outcome of natural disasters, different factors, i.e., uncertain lead time and material quality, incur an additional cost, downgrading the supply chains' efficiency. The optimal inventory decisions are challenging due to the complexity arising from the multi-product, multi-vendor consideration, uncertainty of supplies, and conflicting objectives in sustainable construction supply chains. To fill the existing research gaps, this research presents an operation research modeling framework to minimize the amount of carbon emitted by suppliers' vehicles as well as ordering and holding costs in a post-disaster construction supply chain under the epistemic uncertainty of quality and cost data. Furthermore, the quality of the received material is maximized in the model. Also, the weights of objectives are estimated using two MCDM techniques. A case study is delineated to validate the proposed optimization model and its performance. To make the comparison of the proposed model with the suppliers' efficiency, the DEA model is applied, and sensitivity analysis is presented in this case. The results indicate that supplier selection based on the efficiency of suppliers can culminate in more contractors' satisfaction, although the mathematical model can choose the suppliers with consideration of the project timeline.