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

Seyed Meysam Mousavi | N. Foroozesh | B. Karimi

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URL :   http://research.shahed.ac.ir/WSR/WebPages/Report/PaperView.aspx?PaperID=159250
Date :  2022/01/06
Publish in :    Journal of Environmental Management


Keywords :Green-resilient supply chain, Horizontal collaboration, Route risk, CO2 emission, Generalized interval type-2 fuzzy sets, Robust possibilistic programming, Credibility measure

Abstract :

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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, multiperiod, 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 CO2 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 CO2 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.