Introducing a mixed-integer non-linear fuzzy model for risk management in designing supply chain networks

Nowadays, supply chains play an inevitable role in prompt handling of varying customers’ needs. Administration of a successful supply chain depends on how efficiently the network design is accomplished. Therefore, a supply chain network design problem is considered in this paper. The network addresses an uncertain environment threatened by different risk sources in order to captivate the real world conditions. A mixed-integer non-linear mathematical model is developed in which the uncertainties are represented by the fuzzy set theory. Benders decomposition is then applied to solve the proposed problem; consequently, the model is transformed into a mixed-integer one. Moreover, an interactive resolution method is applied to provide the decision maker with alternative decision plans in regard to different satisfaction degrees. Finally, the accuracy of the proposed model is checked by sensitivity analysis test and its performance is considered by different numerical examples.

► The model covers different uncertainties considering demand, supply, and process sides.
► The potential risks are managed by the fuzzy logic.
► Developing new measures weighted by a multi-attribute decision-making technique.
► Benders decomposition method is applied as the solution approach.