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Interactive fuzzy goal programming for a multi-objective closed-loop logistics network

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Listed:
  • Mehrdad Mehrbod
  • Nan Tu
  • Lixin Miao
  • Dai Wenjing

Abstract

Over the last decade, there has been increased attention to closed-loop logistics networks. Environmental legislation requires companies to be more responsible by collecting used products from customers. Companies can also benefit from savings that are related to recovering and recycling used products. Unlike previous studies, which only consider single products or a single period of time in multi-objective problems, this paper considers a multi-product multi-period closed-loop logistics network with different types of facilities. A multi-objective mixed-integer nonlinear programming formulation is developed to minimize the total cost, the delivery time of new products, and the collection time of used products. Thus, this model better approximates real-life applications of closed-loop logistics problems. Interactive fuzzy goal programming (IFGP) is applied to solve the model for handling multiple objective problems with conflicting objectives and to address the imprecise nature of decision-makers’ aspiration levels for goals. The results from computational experiments performed here show that by changing the upper or lower bound of each objective function, one can obtain a better final solution of the problem and also can provide more options for decision makers to choose from based on their situation. Finally, the utilization rate of facilities is shown to be an important indicator when designing a logistics network. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Mehrdad Mehrbod & Nan Tu & Lixin Miao & Dai Wenjing, 2012. "Interactive fuzzy goal programming for a multi-objective closed-loop logistics network," Annals of Operations Research, Springer, vol. 201(1), pages 367-381, December.
    • Handle: RePEc:spr:annopr:v:201:y:2012:i:1:p:367-381:10.1007/s10479-012-1192-4
    DOI: 10.1007/s10479-012-1192-4
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    References listed on IDEAS

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    Cited by:

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    3. R.S. Rogulin, 2020. "Modeling of Promising Interaction Between a Timber Industry Enterprise and a Commodity Exchange in Russia," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 19(4), pages 489-511.
    4. Anil Jindal & Kuldip Singh Sangwan, 2017. "Multi-objective fuzzy mathematical modelling of closed-loop supply chain considering economical and environmental factors," Annals of Operations Research, Springer, vol. 257(1), pages 95-120, October.
    5. Sebastian Rachuba & Brigitte Werners, 2017. "A fuzzy multi-criteria approach for robust operating room schedules," Annals of Operations Research, Springer, vol. 251(1), pages 325-350, April.
    6. Ozden Tozanli & Gazi Murat Duman & Elif Kongar & Surendra M. Gupta, 2017. "Environmentally Concerned Logistics Operations in Fuzzy Environment: A Literature Survey," Logistics, MDPI, vol. 1(1), pages 1-42, June.
    7. A. Mohammed, 2020. "Towards a sustainable assessment of suppliers: an integrated fuzzy TOPSIS-possibilistic multi-objective approach," Annals of Operations Research, Springer, vol. 293(2), pages 639-668, October.
    8. Yongbo Li & Devika Kannan & P. C. Jha & Kiran Garg & Jyoti Darbari & Neha Agarwal, 2023. "Design of a multi echelon product recovery embeded reverse logistics network for multi products and multi periods," Annals of Operations Research, Springer, vol. 323(1), pages 131-152, April.

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