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A hybrid fuzzy multi-objective model for carpet production planning with reverse logistics under uncertainty

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  • Ghanbarzadeh-Shams, M.
  • Ghasemy Yaghin, R.
  • Sadeghi, A.H.

Abstract

With the presence of ever-rising customers' concerns about environmental impacts, companies are utilizing used products and recyclable materials in their supply chains to manage the products' end-of-life effectively. Effective utilization requires a proper logistical structure to flow used and recovered products throughout the supply chain. In the carpet industry, reverse logistics operations are complex and susceptible to high uncertainty affecting the collection rate, recovered items’ availability, and reverse channel capacity. Besides total cost efficiency, carpet manufacturers and other logistics actors are willing to plan the production and reverse logistics functional areas to optimize sustainability attributes. Armed with these insights, this paper addresses a multi-product, multi-site, and multi-period production planning problem integrated with reverse logistics under uncertainty. A novel fuzzy multi-objective programming model (combining possibility and flexibility) is proposed with chance constraints. Finally, new hybrid fuzzy goal programming is presented to solve the developed model. Numerical study in the carpet industry is included to show the model applicability and sensitivity.

Suggested Citation

  • Ghanbarzadeh-Shams, M. & Ghasemy Yaghin, R. & Sadeghi, A.H., 2022. "A hybrid fuzzy multi-objective model for carpet production planning with reverse logistics under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).
    • Handle: RePEc:eee:soceps:v:83:y:2022:i:c:s0038012122001343
    DOI: 10.1016/j.seps.2022.101344
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    1. Maity, K. & Maiti, M., 2007. "Possibility and necessity constraints and their defuzzification--A multi-item production-inventory scenario via optimal control theory," European Journal of Operational Research, Elsevier, vol. 177(2), pages 882-896, March.
    2. Salahi, Niloofar & Jafari, Mohsen A., 2016. "Energy-Performance as a driver for optimal production planning," Applied Energy, Elsevier, vol. 174(C), pages 88-100.
    3. Akoz, Onur & Petrovic, Dobrila, 2007. "A fuzzy goal programming method with imprecise goal hierarchy," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1427-1433, September.
    4. Dubois, Didier & Fargier, Helene & Fortemps, Philippe, 2003. "Fuzzy scheduling: Modelling flexible constraints vs. coping with incomplete knowledge," European Journal of Operational Research, Elsevier, vol. 147(2), pages 231-252, June.
    5. Bazan, Ehab & Jaber, Mohamad Y. & Zanoni, Simone, 2017. "Carbon emissions and energy effects on a two-level manufacturer-retailer closed-loop supply chain model with remanufacturing subject to different coordination mechanisms," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 394-408.
    6. Wu, Haitao & Xu, Lina & Ren, Siyu & Hao, Yu & Yan, Guoyao, 2020. "How do energy consumption and environmental regulation affect carbon emissions in China? New evidence from a dynamic threshold panel model," Resources Policy, Elsevier, vol. 67(C).
    7. Shiva Zandkarimkhani & Hassan Mina & Mehdi Biuki & Kannan Govindan, 2020. "A chance constrained fuzzy goal programming approach for perishable pharmaceutical supply chain network design," Annals of Operations Research, Springer, vol. 295(1), pages 425-452, December.
    8. Maharjan, Rajali & Hanaoka, Shinya, 2020. "A credibility-based multi-objective temporary logistics hub location-allocation model for relief supply and distribution under uncertainty," Socio-Economic Planning Sciences, Elsevier, vol. 70(C).
    9. Mirzapour Al-e-hashem, S.M.J. & Baboli, A. & Sazvar, Z., 2013. "A stochastic aggregate production planning model in a green supply chain: Considering flexible lead times, nonlinear purchase and shortage cost functions," European Journal of Operational Research, Elsevier, vol. 230(1), pages 26-41.
    10. R. Ghasemy Yaghin & S.M.T. Fatemi Ghomi & S.A. Torabi, 2015. "A hybrid credibility-based fuzzy multiple objective optimisation to differential pricing and inventory policies with arbitrage consideration," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(14), pages 2628-2639, October.
    11. Hans Haake & Stefan Seuring, 2009. "Sustainable procurement of minor items - exploring limits to sustainability," Sustainable Development, John Wiley & Sons, Ltd., vol. 17(5), pages 284-294.
    12. Lin, Jinchai & Fan, Ruguo & Tan, Xianchun & Zhu, Kaiwei, 2021. "Dynamic decision and coordination in a low-carbon supply chain considering the retailer's social preference," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    13. R. Ghasemy Yaghin & M Goh, 2021. "Procurement, production, and price planning under visibility and risk: a generalised Benders decomposition method," International Journal of Production Research, Taylor & Francis Journals, vol. 59(18), pages 5626-5646, September.
    14. Chandra, Pankaj & Fisher, Marshall L., 1994. "Coordination of production and distribution planning," European Journal of Operational Research, Elsevier, vol. 72(3), pages 503-517, February.
    15. D'Ambra, Luigi & Crisci, Anna & Meccariello, Giovanni & Della Ragione, Livia & Palma, Raffaela, 2021. "Evaluation of the social and economic impact of carbon dioxide (CO2) emissions on sustainable mobility using cumulative ordinal models: trend odds model," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
    16. Seyed Mohammad Javad Mirzapour Al-E-Hashem & Armand Baboli & Z. Sazvar, 2013. "A stochastic aggregate production planning model in a green supply chain : Considering flexible lead times, nonlinear purchase and shortage cost functions," Post-Print hal-02313031, HAL.
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