IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i8p4640-d792926.html
   My bibliography  Save this article

Model for Reverse Logistic Problem of Recycling under Stochastic Demand

Author

Listed:
  • Beste Desticioglu

    (Department of Operations Research, Alparslan Defence Science Institute, National Defence University, 06420 Ankara, Turkey)

  • Hatice Calipinar

    (Department of Business Administration, Faculty of Economics and Administrative Science, Hacettepe University, 06800 Ankara, Turkey)

  • Bahar Ozyoruk

    (Department of Industrial Engineering, Faculty of Engineering, Gazi University, 06570 Ankara, Turkey)

  • Erdinc Koc

    (Department of Business Administration, Faculty of Economics and Administrative Science, Bingol University, 12000 Bingol, Turkey)

Abstract

It has become obligatory for businesses to carry out recycling activities in the face of increasing environmental pollution and the danger of depletion of natural resources. The waste collection phase of the recycling process requires interactive transportation that uses a reverse logistics flow from customers to recycling facilities. Businesses need to create appropriate network structures to carry out these activities at minimum cost. This study has developed a model, based on reverse logistics, of collecting products from customers and sending them to warehouses and then to recycling facilities. The chance-constrained programming (CCP) approach was used to regulate the constraints involving stochastic demand in the model. Linearization was performed using the linear approximation method. The cost of transportation from Initial Collection Points (ICP) warehouses to recycling facilities is the most influential component on the objective function. This linearized model was solved by creating different scenarios by changing the standard deviation ratio, reliability level, and warehouse capacities within the scope of sensitivity analysis. In the sensitivity analysis, it was determined that the increase in confidence level and variance negatively affected the objective function. In addition, it has been concluded that the increase in demand has no effect on costs as long as the capacity of the facility is not exceeded.

Suggested Citation

  • Beste Desticioglu & Hatice Calipinar & Bahar Ozyoruk & Erdinc Koc, 2022. "Model for Reverse Logistic Problem of Recycling under Stochastic Demand," Sustainability, MDPI, vol. 14(8), pages 1-19, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4640-:d:792926
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/8/4640/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/8/4640/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Salema, Maria Isabel Gomes & Barbosa-Povoa, Ana Paula & Novais, Augusto Q., 2007. "An optimization model for the design of a capacitated multi-product reverse logistics network with uncertainty," European Journal of Operational Research, Elsevier, vol. 179(3), pages 1063-1077, June.
    2. Shouxu Song & Yongting Tian & Dan Zhou, 2021. "Reverse Logistics Network Design and Simulation for Automatic Teller Machines Based on Carbon Emission and Economic Benefits: A Study of the Anhui Province ATMs Industry," Sustainability, MDPI, vol. 13(20), pages 1-24, October.
    3. Ji-Su Kim & Dong-Ho Lee, 2015. "An integrated approach for collection network design, capacity planning and vehicle routing in reverse logistics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(1), pages 76-85, January.
    4. Chiang, Wen-Chyuan & Urban, Timothy L., 2006. "The stochastic U-line balancing problem: A heuristic procedure," European Journal of Operational Research, Elsevier, vol. 175(3), pages 1767-1781, December.
    5. Jorge Oyola & Halvard Arntzen & David L. Woodruff, 2018. "The stochastic vehicle routing problem, a literature review, part I: models," EURO Journal on Transportation and Logistics, Springer;EURO - The Association of European Operational Research Societies, vol. 7(3), pages 193-221, September.
    6. Vahid Azizi & Guiping Hu, 2021. "A Multi-Stage Stochastic Programming Model for the Multi-Echelon Multi-Period Reverse Logistics Problem," Sustainability, MDPI, vol. 13(24), pages 1-15, December.
    7. Nima Kazemi & Nikunja Mohan Modak & Kannan Govindan, 2019. "A review of reverse logistics and closed loop supply chain management studies published in IJPR: a bibliometric and content analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 57(15-16), pages 4937-4960, August.
    8. Lee, Der-Horng & Dong, Meng, 2009. "Dynamic network design for reverse logistics operations under uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 45(1), pages 61-71, January.
    9. Min, Hokey & Jeung Ko, Hyun & Seong Ko, Chang, 2006. "A genetic algorithm approach to developing the multi-echelon reverse logistics network for product returns," Omega, Elsevier, vol. 34(1), pages 56-69, January.
    10. Urban, Timothy L. & Chiang, Wen-Chyuan, 2006. "An optimal piecewise-linear program for the U-line balancing problem with stochastic task times," European Journal of Operational Research, Elsevier, vol. 168(3), pages 771-782, February.
    11. Fleischmann, Moritz & Bloemhof-Ruwaard, Jacqueline M. & Dekker, Rommert & van der Laan, Erwin & van Nunen, Jo A. E. E. & Van Wassenhove, Luk N., 1997. "Quantitative models for reverse logistics: A review," European Journal of Operational Research, Elsevier, vol. 103(1), pages 1-17, November.
    12. Soleimani, Hamed & Govindan, Kannan, 2014. "Reverse logistics network design and planning utilizing conditional value at risk," European Journal of Operational Research, Elsevier, vol. 237(2), pages 487-497.
    13. A. Charnes & W. W. Cooper, 1963. "Deterministic Equivalents for Optimizing and Satisficing under Chance Constraints," Operations Research, INFORMS, vol. 11(1), pages 18-39, February.
    14. Shuang Li & Nengmin Wang & Zhengwen He & Ada Che & Yungao Ma, 2012. "Design of a Multiobjective Reverse Logistics Network Considering the Cost and Service Level," Mathematical Problems in Engineering, Hindawi, vol. 2012, pages 1-21, October.
    15. Fleischmann, M., 2001. "Reverse Logistics Network Structures and Design," ERIM Report Series Research in Management ERS-2001-52-LIS, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Shraddha Mishra & Surya Prakash Singh, 2022. "Designing dynamic reverse logistics network for post-sale service," Annals of Operations Research, Springer, vol. 310(1), pages 89-118, March.
    17. Cardoso, Sónia R. & Barbosa-Póvoa, Ana Paula F.D. & Relvas, Susana, 2013. "Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 226(3), pages 436-451.
    18. Reddy, K. Nageswara & Kumar, Akhilesh & Choudhary, Alok & Cheng, T. C. Edwin, 2022. "Multi-period green reverse logistics network design: An improved Benders-decomposition-based heuristic approach," European Journal of Operational Research, Elsevier, vol. 303(2), pages 735-752.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marcin Relich, 2023. "A Data-Driven Approach for Improving Sustainable Product Development," Sustainability, MDPI, vol. 15(8), pages 1-18, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Diabat, Ali & Kannan, Devika & Kaliyan, Mathiyazhagan & Svetinovic, Davor, 2013. "An optimization model for product returns using genetic algorithms and artificial immune system," Resources, Conservation & Recycling, Elsevier, vol. 74(C), pages 156-169.
    2. Vahid Azizi & Guiping Hu, 2021. "A Multi-Stage Stochastic Programming Model for the Multi-Echelon Multi-Period Reverse Logistics Problem," Sustainability, MDPI, vol. 13(24), pages 1-15, December.
    3. Van Engeland, Jens & Beliën, Jeroen & De Boeck, Liesje & De Jaeger, Simon, 2020. "Literature review: Strategic network optimization models in waste reverse supply chains," Omega, Elsevier, vol. 91(C).
    4. Felix T.S. Chan & Nan Li & S.H. Chung & Mozafar Saadat, 2017. "Management of sustainable manufacturing systems-a review on mathematical problems," International Journal of Production Research, Taylor & Francis Journals, vol. 55(4), pages 1210-1225, February.
    5. Vahab Vahdat & Mohammad Ali Vahdatzad, 2017. "Accelerated Benders’ Decomposition for Integrated Forward/Reverse Logistics Network Design under Uncertainty," Logistics, MDPI, vol. 1(2), pages 1-21, December.
    6. Agrawal, Saurabh & Singh, Rajesh K. & Murtaza, Qasim, 2015. "A literature review and perspectives in reverse logistics," Resources, Conservation & Recycling, Elsevier, vol. 97(C), pages 76-92.
    7. Xuehong Gao, 2019. "A Novel Reverse Logistics Network Design Considering Multi-Level Investments for Facility Reconstruction with Environmental Considerations," Sustainability, MDPI, vol. 11(9), pages 1-22, May.
    8. Schweiger, Katharina & Sahamie, Ramin, 2013. "A hybrid Tabu Search approach for the design of a paper recycling network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 98-119.
    9. De Rosa, Vincenzo & Gebhard, Marina & Hartmann, Evi & Wollenweber, Jens, 2013. "Robust sustainable bi-directional logistics network design under uncertainty," International Journal of Production Economics, Elsevier, vol. 145(1), pages 184-198.
    10. Ayvaz, Berk & Bolat, Bersam & Aydın, Nezir, 2015. "Stochastic reverse logistics network design for waste of electrical and electronic equipment," Resources, Conservation & Recycling, Elsevier, vol. 104(PB), pages 391-404.
    11. Özcan, Ugur, 2010. "Balancing stochastic two-sided assembly lines: A chance-constrained, piecewise-linear, mixed integer program and a simulated annealing algorithm," European Journal of Operational Research, Elsevier, vol. 205(1), pages 81-97, August.
    12. Toso, Eli Angela V. & Alem, Douglas, 2014. "Effective location models for sorting recyclables in public management," European Journal of Operational Research, Elsevier, vol. 234(3), pages 839-860.
    13. Mota, Bruna & Gomes, Maria Isabel & Carvalho, Ana & Barbosa-Povoa, Ana Paula, 2018. "Sustainable supply chains: An integrated modeling approach under uncertainty," Omega, Elsevier, vol. 77(C), pages 32-57.
    14. Barker, Theresa J. & Zabinsky, Zelda B., 2011. "A multicriteria decision making model for reverse logistics using analytical hierarchy process," Omega, Elsevier, vol. 39(5), pages 558-573, October.
    15. Cardoso, Sónia R. & Barbosa-Póvoa, Ana Paula F.D. & Relvas, Susana, 2013. "Design and planning of supply chains with integration of reverse logistics activities under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 226(3), pages 436-451.
    16. Peng Li & Di Wu, 2021. "A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference," IJERPH, MDPI, vol. 18(9), pages 1-24, April.
    17. Khatami, Maryam & Mahootchi, Masoud & Farahani, Reza Zanjirani, 2015. "Benders’ decomposition for concurrent redesign of forward and closed-loop supply chain network with demand and return uncertainties," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 79(C), pages 1-21.
    18. Vahdani, Behnam & Tavakkoli-Moghaddam, Reza & Modarres, Mohammad & Baboli, Armand, 2012. "Reliable design of a forward/reverse logistics network under uncertainty: A robust-M/M/c queuing model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(6), pages 1152-1168.
    19. Keyvanshokooh, Esmaeil & Ryan, Sarah M. & Kabir, Elnaz, 2016. "Hybrid robust and stochastic optimization for closed-loop supply chain network design using accelerated Benders decomposition," European Journal of Operational Research, Elsevier, vol. 249(1), pages 76-92.
    20. Melo, M.T. & Nickel, S. & Saldanha-da-Gama, F., 2009. "Facility location and supply chain management - A review," European Journal of Operational Research, Elsevier, vol. 196(2), pages 401-412, July.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:8:p:4640-:d:792926. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.