Green-resilient supply chain network design for perishable products considering route risk and horizontal collaboration under robust interval-valued type-2 fuzzy uncertainty: A case study in food industry. (1st April 2022) - Foroozesh, N.; Karimi, B.; Mousavi, S.M.
Abstract: A green and resilient (G-Resilient) supply chain network is designed for perishable products under disruption risks and epistemic uncertainties. This study aims to minimize effects of the disruption by presenting new strategies, such as multiple sourcing, financial suppliers, horizontal collaboration, route risk, and coverage radius, in designing a new multi-objective mixed-integer linear programming model for multi-product, multi-period, multi-modal G-Resilient supply chain. Then, a novel robust possibilistic programming (RPP) approach is presented using credibility measure and membership functions of generalized interval-valued type-2 fuzzy variables to face the epistemic uncertainties, such as supply capacity of facilities, customer demand, transportation cost, and C O 2 emission factor, in the proposed mathematical model. An improved version of augmented ε-constraint method (AUGMECON2) is also employed to produce separate Pareto-optimal solutions. Moreover, the study compares the proposed RPP with possibilistic chance-constrained programming model and illustrates its advantages; in the standard deviation of C O 2 emission objective function, its performance has improved by about 44.91%. Finally, the model's performance has been verified by a real case study in the food industry, and managerial implications have been provided. Highlights: Proposing a new MOMILP model for green-resilient supply chain network design. Presenting route risk and horizontal collaboration for perishable products. Introducing a new generalized interval type-2 fuzzy-robust solution approach. Considering different scenarios by regarding disruption risks in reality. Implementing proposed mathematical model to a real case study in food industry.