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Multi-objective Fuzzy Programming of Closed-Loop Supply Chain Considering Sustainable Measures

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Abstract

The substantial impact of environmental and social issues on business performance highlights the significant role of sustainability in supply chain network design problems. The innate uncertainty of the problem factors such as customer demand and return rates requires an integrated approach to deal with the problem. This paper aims to design a closed-loop supply chain (CLSC) network considering both sustainability and uncertainty issues. Fuzzy programming is used to address the uncertainty in this study. A fuzzy multi-objective mixed-integer linear programming is developed to simultaneously optimize a sustainable CLSC network. The objectives are considered to be the total costs and the environmental impacts minimization and social benefits maximization. Three pillars of sustainability (cost, environmental, and social) are taken into account in network design. A three-phased fuzzy solution approach is developed to solve this model. To examine the significance of the proposed model and the solution approach, a computational experiment is conducted. The results approve the applicability of the proposed approach and the feasibility of the solution methodology. Results also show that the proposed model presents a systematic framework that enables the management to obtain a satisfactory solution by adjusting the search direction.

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Acknowledgements

This paper research has been supported by a grant (No 155147-2013) from the Natural Sciences and Engineering Research Council of Canada (NSERC).

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  1. University of Regina, Regina, SK, Canada

    Ehsan Pourjavad & Rene V. Mayorga

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  1. Ehsan Pourjavad
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Correspondence to Rene V. Mayorga.

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Pourjavad, E., Mayorga, R.V. Multi-objective Fuzzy Programming of Closed-Loop Supply Chain Considering Sustainable Measures. Int. J. Fuzzy Syst. 21, 655–673 (2019). https://doi.org/10.1007/s40815-018-0551-y

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