Abstract
In this study, There is a mixed-integer nonlinear program (MINLP) for a two-echelon supply chain that focuses on supplier location, supplier selection and order allocation with green constraints. This bi-objective model is designed and modeled with the aim of coordinating inventory and transportation among suppliers and warehouses and tries to simultaneously meet the targets of minimizing total costs and carbon dioxide emissions of polluting gas in transportation. Since some of the important parameters in this model are considered uncertain, the scenario-based analysis is proposed to deal with uncertainty. Thirty numerical examples with different values and various sizes are solved by applying two methods of MODM, LP metrics, and Multi-choice goal programming with utility functions (MCGP-U) and their results are compared with one of the soft computing methods, Genetic algorithm. TOPSIS, Coefficient of Variation (CV) and One-way analysis of variance (ANOVA) methods are employed for the comprehensive comparison of these numerical examples. Finally, the sensitivity analysis method and Tornado diagram are applied to analyze the effect of variations of the model’s inputs on the results of the model.
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Hemmati, M., Pasandideh, S.H.R. A bi-objective supplier location, supplier selection and order allocation problem with green constraints: scenario-based approach. J Ambient Intell Human Comput 12, 8205–8228 (2021). https://doi.org/10.1007/s12652-020-02555-1
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DOI: https://doi.org/10.1007/s12652-020-02555-1