IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v122y2024ics0305048323001032.html
   My bibliography  Save this article

An oracle-based algorithm for robust planning of production routing problems in closed-loop supply chains of beverage glass bottles

Author

Listed:
  • Borumand, Ali
  • Marandi, Ahmadreza
  • Nookabadi, Ali S.
  • Atan, Zümbül

Abstract

The demand for glass bottles is exhibiting an upward trend over time. The manufacturing of glass bottles is costlier in terms of time and resources and is associated with a higher level of heat generation and environmental pollution compared to recycling processes. In response to the aforementioned challenges, companies that use glass bottles need to implement strategies to manage their reverse supply chains in conjunction with their traditional supply chains, as the economic and environmental benefits of returned products are unquestionable. Closed-loop supply chains (CLSCs) integrate forward and reverse flows of products and information. This integration helps companies to have a broader view of the whole chain. Despite these advantages, managing CLSCs can be challenging as they are exposed to many uncertainties regarding supply and demand processes, travel times, and quantity/quality of returned products.

Suggested Citation

  • Borumand, Ali & Marandi, Ahmadreza & Nookabadi, Ali S. & Atan, Zümbül, 2024. "An oracle-based algorithm for robust planning of production routing problems in closed-loop supply chains of beverage glass bottles," Omega, Elsevier, vol. 122(C).
    • Handle: RePEc:eee:jomega:v:122:y:2024:i:c:s0305048323001032
    DOI: 10.1016/j.omega.2023.102939
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305048323001032
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.omega.2023.102939?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhi Chen & Melvyn Sim & Peng Xiong, 2020. "Robust Stochastic Optimization Made Easy with RSOME," Management Science, INFORMS, vol. 66(8), pages 3329-3339, August.
    2. Dimitris Bertsimas & Iain Dunning, 2016. "Multistage Robust Mixed-Integer Optimization with Adaptive Partitions," Operations Research, INFORMS, vol. 64(4), pages 980-998, August.
    3. Cheng, Chun & Adulyasak, Yossiri & Rousseau, Louis-Martin, 2021. "Robust facility location under demand uncertainty and facility disruptions," Omega, Elsevier, vol. 103(C).
    4. Phebe Vayanos & Qing Jin & George Elissaios, 2022. "ROC++: Robust Optimization in C++," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 2873-2888, November.
    5. Zhalechian, M. & Tavakkoli-Moghaddam, R. & Zahiri, B. & Mohammadi, M., 2016. "Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 182-214.
    6. Stacey, Nicholas & Edoka, Ijeoma & Hofman, Karen & Swart, Elizabeth C & Popkin, Barry & Ng, Shu Wen, 2021. "Changes in beverage purchases following the announcement and implementation of South Africa's Health Promotion Levy: an observational study," LSE Research Online Documents on Economics 109878, London School of Economics and Political Science, LSE Library.
    7. Chrysanthos E. Gounaris & Wolfram Wiesemann & Christodoulos A. Floudas, 2013. "The Robust Capacitated Vehicle Routing Problem Under Demand Uncertainty," Operations Research, INFORMS, vol. 61(3), pages 677-693, June.
    8. Iassinovskaia, Galina & Limbourg, Sabine & Riane, Fouad, 2017. "The inventory-routing problem of returnable transport items with time windows and simultaneous pickup and delivery in closed-loop supply chains," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 570-582.
    9. Matthews, Logan R. & Gounaris, Chrysanthos E. & Kevrekidis, Ioannis G., 2019. "Designing networks with resiliency to edge failures using two-stage robust optimization," European Journal of Operational Research, Elsevier, vol. 279(3), pages 704-720.
    10. Ben-Tal, Aharon & Chung, Byung Do & Mandala, Supreet Reddy & Yao, Tao, 2011. "Robust optimization for emergency logistics planning: Risk mitigation in humanitarian relief supply chains," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1177-1189, September.
    11. Grani A. Hanasusanto & Daniel Kuhn & Wolfram Wiesemann, 2015. "K -Adaptability in Two-Stage Robust Binary Programming," Operations Research, INFORMS, vol. 63(4), pages 877-891, August.
    12. Amir Ardestani-Jaafari & Erick Delage, 2018. "The Value of Flexibility in Robust Location–Transportation Problems," Transportation Science, INFORMS, vol. 52(1), pages 189-209, January.
    13. Krzysztof Postek & Dick den Hertog, 2016. "Multistage Adjustable Robust Mixed-Integer Optimization via Iterative Splitting of the Uncertainty Set," INFORMS Journal on Computing, INFORMS, vol. 28(3), pages 553-574, August.
    14. Shuai Deng & Yanhui Li & Hao Guo & Bailing Liu, 2016. "Solving a Closed-Loop Location-Inventory-Routing Problem with Mixed Quality Defects Returns in E-Commerce by Hybrid Ant Colony Optimization Algorithm," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-12, June.
    15. Polo, Andrés & Peña, Numar & Muñoz, Dairo & Cañón, Adrián & Escobar, John Willmer, 2019. "Robust design of a closed-loop supply chain under uncertainty conditions integrating financial criteria," Omega, Elsevier, vol. 88(C), pages 110-132.
    16. Zhou, Yu & Xiong, Yu & Jin, Minyue, 2021. "Less is more: Consumer education in a closed-loop supply chain with remanufacturing," Omega, Elsevier, vol. 101(C).
    17. Omar El Housni & Vineet Goyal, 2021. "On the Optimality of Affine Policies for Budgeted Uncertainty Sets," Mathematics of Operations Research, INFORMS, vol. 46(2), pages 674-711, May.
    18. De, Manoranjan & Giri, B.C., 2020. "Modelling a closed-loop supply chain with a heterogeneous fleet under carbon emission reduction policy," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    19. Yipei Zhang & Ada Che & Feng Chu, 2022. "Improved model and efficient method for bi-objective closed-loop food supply chain problem with returnable transport items," International Journal of Production Research, Taylor & Francis Journals, vol. 60(3), pages 1051-1068, February.
    20. David Simchi-Levi & Nikolaos Trichakis & Peter Yun Zhang, 2019. "Designing Response Supply Chain Against Bioattacks," Operations Research, INFORMS, vol. 67(5), pages 1246-1268, September.
    21. Arabi, Mahsa & Gholamian, Mohammad Reza, 2023. "Resilient closed-loop supply chain network design considering quality uncertainty: A case study of stone quarries," Resources Policy, Elsevier, vol. 80(C).
    22. Yanıkoğlu, İhsan & Gorissen, Bram L. & den Hertog, Dick, 2019. "A survey of adjustable robust optimization," European Journal of Operational Research, Elsevier, vol. 277(3), pages 799-813.
    23. A. Ben-Tal & A. Nemirovski, 1998. "Robust Convex Optimization," Mathematics of Operations Research, INFORMS, vol. 23(4), pages 769-805, November.
    24. Liao, Haolan & Zhang, Qingyu & Shen, Neng & Nie, Yongyou & Li, Lu, 2021. "Coordination between forward and reverse production streams for maximum profitability," Omega, Elsevier, vol. 104(C).
    25. Ahmed Timoumi & Narendra Singh & Subodha Kumar, 2021. "Is Your Retailer a Friend or Foe: When Should the Manufacturer Allow Its Retailer to Refurbish?," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 2814-2839, September.
    26. M A Colchero & Carlos Manuel Guerrero-López & Mariana Molina & Juan Angel Rivera, 2016. "Beverages Sales in Mexico before and after Implementation of a Sugar Sweetened Beverage Tax," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-8, September.
    27. Galina Iassinovskaia & Sabine Limbourg & Fouad Riane, 2017. "The inventory-routing problem of returnable transport items with time windows and simultaneous pickup and delivery in closed-loop supply chains," Post-Print hal-04333507, HAL.
    28. Ali Pedram & Shahryar Sorooshian & Freselam Mulubrhan & Afshin Abbaspour, 2023. "Incorporating Vehicle-Routing Problems into a Closed-Loop Supply Chain Network Using a Mixed-Integer Linear-Programming Model," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    29. Dominguez, Roberto & Cannella, Salvatore & Framinan, Jose M., 2021. "Remanufacturing configuration in complex supply chains," Omega, Elsevier, vol. 101(C).
    30. Govindan, Kannan & Salehian, Farhad & Kian, Hadi & Hosseini, Seyed Teimoor & Mina, Hassan, 2023. "A location-inventory-routing problem to design a circular closed-loop supply chain network with carbon tax policy for achieving circular economy: An augmented epsilon-constraint approach," International Journal of Production Economics, Elsevier, vol. 257(C).
    31. Angelos Georghiou & Angelos Tsoukalas & Wolfram Wiesemann, 2020. "A Primal–Dual Lifting Scheme for Two-Stage Robust Optimization," Operations Research, INFORMS, vol. 68(2), pages 572-590, March.
    32. Ward Romeijnders & Krzysztof Postek, 2021. "Piecewise Constant Decision Rules via Branch-and-Bound Based Scenario Detection for Integer Adjustable Robust Optimization," INFORMS Journal on Computing, INFORMS, vol. 33(1), pages 390-400, January.
    33. Postek, Krzysztof & den Hertog, Dick & Kind, Jarl & Pustjens, Chris, 2019. "Adjustable robust strategies for flood protection," Omega, Elsevier, vol. 82(C), pages 142-154.
    34. Qiu, Yuzhuo & Ni, Ming & Wang, Liang & Li, Qinqin & Fang, Xuanjing & Pardalos, Panos M., 2018. "Production routing problems with reverse logistics and remanufacturing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 87-100.
    Full references (including those not matched with items on IDEAS)

    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. Bakker, Hannah & Dunke, Fabian & Nickel, Stefan, 2020. "A structuring review on multi-stage optimization under uncertainty: Aligning concepts from theory and practice," Omega, Elsevier, vol. 96(C).
    2. Cohen, Izack & Postek, Krzysztof & Shtern, Shimrit, 2023. "An adaptive robust optimization model for parallel machine scheduling," European Journal of Operational Research, Elsevier, vol. 306(1), pages 83-104.
    3. Farough Motamed Nasab & Zukui Li, 2023. "Multistage Adaptive Robust Binary Optimization: Uncertainty Set Lifting versus Partitioning through Breakpoints Optimization," Mathematics, MDPI, vol. 11(18), pages 1-24, September.
    4. Angelos Georghiou & Angelos Tsoukalas & Wolfram Wiesemann, 2020. "A Primal–Dual Lifting Scheme for Two-Stage Robust Optimization," Operations Research, INFORMS, vol. 68(2), pages 572-590, March.
    5. Abbas Khademi & Ahmadreza Marandi & Majid Soleimani-damaneh, 2024. "A new dual-based cutting plane algorithm for nonlinear adjustable robust optimization," Journal of Global Optimization, Springer, vol. 89(3), pages 559-595, July.
    6. Christoph Buchheim & Jannis Kurtz, 2018. "Robust combinatorial optimization under convex and discrete cost uncertainty," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(3), pages 211-238, September.
    7. Jiu, Song, 2022. "Robust omnichannel retail operations with the implementation of ship-from-store," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    8. Feng, Wei & Feng, Yiping & Zhang, Qi, 2021. "Multistage robust mixed-integer optimization under endogenous uncertainty," European Journal of Operational Research, Elsevier, vol. 294(2), pages 460-475.
    9. Yanıkoğlu, İhsan & Gorissen, Bram L. & den Hertog, Dick, 2019. "A survey of adjustable robust optimization," European Journal of Operational Research, Elsevier, vol. 277(3), pages 799-813.
    10. Anirudh Subramanyam & Frank Mufalli & José M. Lí?nez-Aguirre & Jose M. Pinto & Chrysanthos E. Gounaris, 2021. "Robust Multiperiod Vehicle Routing Under Customer Order Uncertainty," Operations Research, INFORMS, vol. 69(1), pages 30-60, January.
    11. Nicolas Kämmerling & Jannis Kurtz, 2020. "Oracle-based algorithms for binary two-stage robust optimization," Computational Optimization and Applications, Springer, vol. 77(2), pages 539-569, November.
    12. Phebe Vayanos & Qing Jin & George Elissaios, 2022. "ROC++: Robust Optimization in C++," INFORMS Journal on Computing, INFORMS, vol. 34(6), pages 2873-2888, November.
    13. Lee, Junhyeok & Moon, Ilkyeong, 2024. "A decomposition approach for robust omnichannel retail operations considering the third-party platform channel," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 184(C).
    14. Cambier, Adrien & Chardy, Matthieu & Figueiredo, Rosa & Ouorou, Adam & Poss, Michael, 2022. "Optimizing subscriber migrations for a telecommunication operator in uncertain context," European Journal of Operational Research, Elsevier, vol. 298(1), pages 308-321.
    15. Walid Ben-Ameur & Adam Ouorou & Guanglei Wang & Mateusz Żotkiewicz, 2018. "Multipolar robust optimization," EURO Journal on Computational Optimization, Springer;EURO - The Association of European Operational Research Societies, vol. 6(4), pages 395-434, December.
    16. Aliakbari Sani, Sajad & Bahn, Olivier & Delage, Erick, 2022. "Affine decision rule approximation to address demand response uncertainty in smart Grids’ capacity planning," European Journal of Operational Research, Elsevier, vol. 303(1), pages 438-455.
    17. Zhang, Liu & Zheng, Zhong & Chai, Yi & Zhang, Kaitian & Lian, Xiaoyuan & Zhang, Kai & Zhao, Liuqiang, 2024. "Enhancing robustness: Multi-stage adaptive robust scheduling of oxygen systems in steel enterprises under demand uncertainty," Applied Energy, Elsevier, vol. 359(C).
    18. Aakil M. Caunhye & Nazli Yonca Aydin & H. Sebnem Duzgun, 2020. "Robust post-disaster route restoration," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 42(4), pages 1055-1087, December.
    19. Tianqi Liu & Francisco Saldanha-da-Gama & Shuming Wang & Yuchen Mao, 2022. "Robust Stochastic Facility Location: Sensitivity Analysis and Exact Solution," INFORMS Journal on Computing, INFORMS, vol. 34(5), pages 2776-2803, September.
    20. van Eekelen, Wouter, 2023. "Distributionally robust views on queues and related stochastic models," Other publications TiSEM 9b99fc05-9d68-48eb-ae8c-9, Tilburg University, School of Economics and Management.

    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:eee:jomega:v:122:y:2024:i:c:s0305048323001032. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.