Multi-objective model for supplier selection and order allocation problem with fuzzy parameters

•Models a multi-objective supplier selection problem.•Considers fuzzy constraints and fuzzy coefficients in the model.•Develops a weighted additive function to turn the model to a single-objective model.•Applies a resolution method to solve the single-objective model. Disasters, such as Coronavirus pandemic and Japan’s earthquake and tsunami, negatively hits firms and markets. It may drastically increase market demand for some products, or decrease suppliers’ ability to supply them at right quantity, quality and time. This uncertainty can be modeled with the fuzzy set theory that is less data-demanding than the probability theory. When a supplier selection problem (SSP) is formulated by fuzzy mathematical programming technique, we have to address two issues: (1) fuzzy constraints, due to the uncertainty in demand and supply capacity, and (2) fuzzy coefficients, due to the uncertainty in defective and late delivery rates, etc. In this study, we develop a fuzzy multi-objective model for a SSP to address these two issues. We first develop a weighted additive function to transform the fuzzy multi-objective model to a fuzzy single-objective model that can effectively consider the decision makers’ preferences. Then, a resolution method is applied to solve the single-objective model with fuzzy parameters.