An integrated supply chain configuration model and procurement management under uncertainty: A set-based robust optimization methodology

Abstract Supply chain configuration and supplier selection are two significant strategic decision making problems in supply chain management. In order to tackle the uncertain environment in these two problems, we propose an integrated mathematical programming model based on robust optimization theory. The framework of the proposed supply chain network involves a forward flow from heterogeneous capacitated suppliers offering price discounts to customers, and also a reverse flow from customer zones to disposal centers or production facilities. The objective function of the model is to minimize the total cost of the supply chain network by determining a set of best suppliers, order allocation to selected suppliers, the location of facilities in each layer and transportation quantities between them. Moreover, to measure the imprecise input parameters, according to three types of uncertainty sets, the robust counterparts of the model have been developed. Finally, to validate the robust model, the eventual optimal solutions are compared with the deterministic model, and numerical studies have been implemented along with sensitivity analysis.