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Classification of Factors Associated with a Closed-Loop Supply Chain System, Their Modelling Methods and Strategies

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Supply Chain Intelligence

Part of the book series: Management and Industrial Engineering ((MINEN))

Abstract

Environmental impact of the industries has been one of the primary concerns of the society today due to increased carbon emission and non-sustainability in their open-end supply chain systems. Closed-loop supply chain system (CLSC) is an improved system often suggested by researchers to enhance sustainability and lower environmental degradation by closing the loop of the product lifecycle and encouraging product returns and other green activities. The concept was strengthened by the introduction of various policies and regulations by the government for the sake of maintaining the health of the environment. In this paper, a thorough investigation of the CLSC system and categories/groups of factors influencing the optimal parameters of a CLSC system have been reported. Modelling of CLSC strategies involves different uncertainty problems which are required to be solved using different mathematical models. These uncertainty problems are governed by the varying numbers assigned to the uncertainty factors. This paper gives an account of various modelling methods and solution strategies commonly used in the research of CLSC systems for solving the uncertainty problems and analyze different aspects of the practical system for an optimized supply chain system.

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  1. Birla Institute of Technology, Mesra, Ranchi, India

    Hridayjit Kalita & Kaushik Kumar

  2. University of Aveiro, Aveiro, Portugal

    J. Paulo Davim

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  1. Hridayjit Kalita
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  2. Kaushik Kumar
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  1. Department of Mechanical Engineering, Birla Institute of Technology, Mesra, Ranchi, Jharkhand, India

    Kaushik Kumar

  2. Department of Mechanical Engineering, University of Aveiro, Aveiro, Portugal

    J. Paulo Davim

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Kalita, H., Kumar, K., Davim, J.P. (2020). Classification of Factors Associated with a Closed-Loop Supply Chain System, Their Modelling Methods and Strategies. In: Kumar, K., Davim, J. (eds) Supply Chain Intelligence. Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-46425-7_2

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