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Fuzzy Optimisation Approach to Supply Chain Distribution Network for Product Value Recovery

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Book cover Proceedings of Fourth International Conference on Soft Computing for Problem Solving

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 336))

Abstract

Efficient integration of forward and reverse logistics network is significant for optimising the economic and ecological value of a closed-loop supply chain network (CLSCN). There is also a high measure of uncertainty involved in such networks and must be handled appropriately in the decision-making process. In this study, we propose a fuzzy optimisation model for improving a CLSCN for handling end-of-life (EOL) and end-of-use (EOU) products. Manufacturer uses fabricated components obtained from the recovery processes and procures new components from external suppliers to assemble new products. Suppliers are evaluated using ANP and are assigned weights. Environmental concerns are also addressed by the model by ensuring that the carbon emission due to transportation does not exceed the permissible carbon cap. To achieve this, hybrid distribution-cum-collection centres (HDC) are grouped into optimal clusters. Products are carried along optimal routes within these clusters using travelling salesman problem (TSP). A fuzzy multi-objective mixed integer linear programming model is proposed which aims at minimising cost of the network and maximising weights of suppliers. A case study of printers is considered to validate the model.

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References

  1. Srivastava, Samir K.: Green supply-chain management: a state-of-the-art literature review. Int. J. Manage. Rev. 9(1), 53–80 (2007)

    Article  Google Scholar 

  2. Akçalı, Elif, Çetinkaya, Sila, Üster, Halit: Network design for reverse and closed-loop supply chains: an annotated bibliography of models and solution approaches. Networks 53(3), 231–248 (2009)

    Article  MATH  Google Scholar 

  3. Akçalı, E., Cetinkaya, S.: Quantitative models for inventory and production planning in closed-loop supply chains. Int. J. Prod. Res. 49(8), 2373–2407 (2011)

    Article  Google Scholar 

  4. Guide Jr, V., Daniel, R., Van Wassenhove, L.N.: OR FORUM-the evolution of closed-loop supply chain research. Oper. Res. 57(1), 10–18 (2009)

    Article  MATH  Google Scholar 

  5. Mutha, Akshay, Pokharel, Shaligram: Strategic network design for reverse logistics and remanufacturing using new and old product modules. Comput. Ind. Eng. 56(1), 334–346 (2009)

    Article  Google Scholar 

  6. Paksoy, T., Bektaş, T., Özceylan, E.: Operational and environmental performance measures in a multi-product closed-loop supply chain. Transp. Res. Part E: Logistics Transp. Rev. 47(4), 532–546 (2011)

    Article  Google Scholar 

  7. Amin, S.H., Zhang, G.: A proposed mathematical model for closed-loop network configuration based on product life cycle. Int. J. Adv. Manuf. Technol. 58(5–8), 791–801 (2012)

    Article  MathSciNet  Google Scholar 

  8. Govindan, Kannan, Khodaverdi, Roohollah, Jafarian, Ahmad: A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. J. Clean. Prod. 47, 345–354 (2013)

    Article  Google Scholar 

  9. Kannan, Devika, Khodaverdi, Roohollah, Olfat, Laya, Jafarian, Ahmad, Diabat, Ali: Integrated fuzzy multi criteria decision making method and multi-objective programming approach for supplier selection and order allocation in a green supply chain. J. Clean. Prod. 47, 355–367 (2013)

    Article  Google Scholar 

  10. Shi, J., Zhang, G., Sha, J.: Optimal production planning for a multi-product closed loop system with uncertain demand and return. Comput Oper. Res. 38(3), 641–650 (2011)

    Article  MATH  MathSciNet  Google Scholar 

  11. Özceylan, Eren, Paksoy, Turan: A mixed integer programming model for a closed-loop supply-chain network. Int. J. Prod. Res. 51(3), 718–734 (2013)

    Article  Google Scholar 

  12. Amin, S.H., Zhang, G.: A three-stage model for closed-loop supply chain configuration under uncertainty. Int. J. Prod. Res. 51(5), 1405–1425 (2013)

    Article  Google Scholar 

  13. Bellman, R.E., Zadeh, L.A.: Decision-making in a fuzzy environment. Manage. sci. 17(4), B-141 (1970)

    Article  MathSciNet  Google Scholar 

  14. Zimmermann, H.-J.: Fuzzy programming and linear programming with several objective functions. Fuzzy Sets Syst. 1(1), 45–55 (1978)

    Article  MATH  Google Scholar 

  15. Liang, Tien-Fu: Fuzzy multi-objective production/distribution planning decisions with multi-product and multi-time period in a supply chain. Comput. Ind. Eng. 55(3), 676–694 (2008)

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Operational Research, University of Delhi, Delhi, India

    Jyoti Dhingra Darbari, Vernika Agarwal & P. C. Jha

Authors
  1. Jyoti Dhingra Darbari
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  2. Vernika Agarwal
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  3. P. C. Jha
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Corresponding author

Correspondence to Jyoti Dhingra Darbari .

Editor information

Editors and Affiliations

  1. Mathematics, National Institute of Technology Silchar, Silchar, Assam, India

    Kedar Nath Das

  2. Department of Mathematics, Indian Institute of Technology Roorkee, Roorkee, Uttarakhand, India

    Kusum Deep

  3. Department of Paper Technology, Indian Institute of Technology Roorkee, Roorkee, India

    Millie Pant

  4. South Asian University, New Delhi, India

    Jagdish Chand Bansal

  5. Department of Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya Nagar

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Darbari, J.D., Agarwal, V., Jha, P.C. (2015). Fuzzy Optimisation Approach to Supply Chain Distribution Network for Product Value Recovery. In: Das, K., Deep, K., Pant, M., Bansal, J., Nagar, A. (eds) Proceedings of Fourth International Conference on Soft Computing for Problem Solving. Advances in Intelligent Systems and Computing, vol 336. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2220-0_40

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  • DOI: https://doi.org/10.1007/978-81-322-2220-0_40

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2219-4

  • Online ISBN: 978-81-322-2220-0

  • eBook Packages: EngineeringEngineering (R0)

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