IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i18p2325-d639022.html
   My bibliography  Save this article

A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies

Author

Listed:
  • Cong Wang

    (School of Economics & Management, Southeast University, Nanjing 211189, China
    School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Zhongxiu Peng

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

  • Xijun Xu

    (School of Maritime Economics and Management, Dalian Maritime University, Dalian 116026, China)

Abstract

To identify the impact of low-carbon policies on the location-routing problem (LRP) with cargo splitting (LRPCS), this paper first constructs the bi-level programming model of LRPCS. On this basis, the bi-level programming models of LRPCS under four low-carbon policies are constructed, respectively. The upper-level model takes the engineering construction department as the decision-maker to decide on the distribution center’s location. The lower-level model takes the logistics and distribution department as the decision-maker to make decisions on the vehicle distribution route’s scheme. Secondly, the hybrid algorithm of Ant Colony Optimization and Tabu Search (ACO-TS) is designed, and an example is introduced to verify the model’s and algorithm’s effectiveness. Finally, multiple sets of experiments are designed to explore the impact of various low-carbon policies on the decision-making of the LRPCS. The experimental results show that the influence of the carbon tax policy is the greatest, the carbon trading and carbon offset policy have a certain impact on the decision-making of the LRPCS, and the influence of the emission cap policy is the least. Based on this, we provide the relevant low-carbon policies advice and management implications.

Suggested Citation

  • Cong Wang & Zhongxiu Peng & Xijun Xu, 2021. "A Bi-Level Programming Approach to the Location-Routing Problem with Cargo Splitting under Low-Carbon Policies," Mathematics, MDPI, vol. 9(18), pages 1-34, September.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:18:p:2325-:d:639022
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/18/2325/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/18/2325/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bektas, Tolga & Laporte, Gilbert, 2011. "The Pollution-Routing Problem," Transportation Research Part B: Methodological, Elsevier, vol. 45(8), pages 1232-1250, September.
    2. Shuanglin Li & Kok Lay Teo, 2019. "Post-disaster multi-period road network repair: work scheduling and relief logistics optimization," Annals of Operations Research, Springer, vol. 283(1), pages 1345-1385, December.
    3. Zhang, Lingye & Lu, Jing & Yang, Zaili, 2021. "Optimal scheduling of emergency resources for major maritime oil spills considering time-varying demand and transportation networks," European Journal of Operational Research, Elsevier, vol. 293(2), pages 529-546.
    4. Juan Guillermo Urzúa-Morales & Juan Pedro Sepulveda-Rojas & Miguel Alfaro & Guillermo Fuertes & Rodrigo Ternero & Manuel Vargas, 2020. "Logistic Modeling of the Last Mile: Case Study Santiago, Chile," Sustainability, MDPI, vol. 12(2), pages 1-18, January.
    5. Longlong Leng & Yanwei Zhao & Zheng Wang & Hongwei Wang & Jingling Zhang, 2018. "Shared Mechanism-Based Self-Adaptive Hyperheuristic for Regional Low-Carbon Location-Routing Problem with Time Windows," Mathematical Problems in Engineering, Hindawi, vol. 2018, pages 1-21, December.
    6. Gu, Xiaoyu & Zhou, Li & Huang, Hongfu & Shi, Xiutian & Ieromonachou, Petros, 2021. "Electric vehicle battery secondary use under government subsidy: A closed-loop supply chain perspective," International Journal of Production Economics, Elsevier, vol. 234(C).
    7. Çağrı Koç, 2019. "Analysis of vehicle emissions in location-routing problem," Flexible Services and Manufacturing Journal, Springer, vol. 31(1), pages 1-33, March.
    8. Ma, Shigui & He, Yong & Gu, Ran & Li, Shanshan, 2021. "Sustainable supply chain management considering technology investments and government intervention," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    9. Shirley (Rong) Li & Burcu B Keskin, 2014. "Bi-criteria dynamic location-routing problem for patrol coverage," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(11), pages 1711-1725, November.
    10. Schyns, M., 2015. "An ant colony system for responsive dynamic vehicle routing," European Journal of Operational Research, Elsevier, vol. 245(3), pages 704-718.
    11. Zhang, Bo & Li, Hui & Li, Shengguo & Peng, Jin, 2018. "Sustainable multi-depot emergency facilities location-routing problem with uncertain information," Applied Mathematics and Computation, Elsevier, vol. 333(C), pages 506-520.
    12. Micheli, Guido J.L. & Mantella, Fabio, 2018. "Modelling an environmentally-extended inventory routing problem with demand uncertainty and a heterogeneous fleet under carbon control policies," International Journal of Production Economics, Elsevier, vol. 204(C), pages 316-327.
    13. Ji Ung Sun, 2015. "An Endosymbiotic Evolutionary Algorithm for the Hub Location-Routing Problem," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-11, July.
    14. Longlong Leng & Yanwei Zhao & Zheng Wang & Jingling Zhang & Wanliang Wang & Chunmiao Zhang, 2019. "A Novel Hyper-Heuristic for the Biobjective Regional Low-Carbon Location-Routing Problem with Multiple Constraints," Sustainability, MDPI, vol. 11(6), pages 1-31, March.
    15. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "The impact of depot location, fleet composition and routing on emissions in city logistics," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 81-102.
    16. Claudia Archetti & Martin W. P. Savelsbergh & M. Grazia Speranza, 2006. "Worst-Case Analysis for Split Delivery Vehicle Routing Problems," Transportation Science, INFORMS, vol. 40(2), pages 226-234, May.
    17. S. L. Hakimi, 1964. "Optimum Locations of Switching Centers and the Absolute Centers and Medians of a Graph," Operations Research, INFORMS, vol. 12(3), pages 450-459, June.
    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. Hongli Zhu & Congcong Liu & Yongming Song, 2022. "A Bi-Level Programming Model for the Integrated Problem of Low Carbon Supplier Selection and Transportation," Sustainability, MDPI, vol. 14(16), pages 1-11, August.

    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. Jaller, Miguel & Pahwa, Anmol, 2023. "Coping with the Rise of E-commerce Generated Home Deliveries through Innovative Last-mile Technologies and Strategies," Institute of Transportation Studies, Working Paper Series qt5t76x0kh, Institute of Transportation Studies, UC Davis.
    2. Zhongxiu Peng & Cong Wang & Wenqing Xu & Jinsong Zhang, 2022. "Research on Location-Routing Problem of Maritime Emergency Materials Distribution Based on Bi-Level Programming," Mathematics, MDPI, vol. 10(8), pages 1-23, April.
    3. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    4. Mohammad Asghari & Seyed Mohammad Javad Mirzapour Al-E-Hashem, 2021. "Green vehicle routing problem: A state-of-the-art review," Post-Print hal-03182944, HAL.
    5. Ehmke, Jan Fabian & Campbell, Ann M. & Thomas, Barrett W., 2018. "Optimizing for total costs in vehicle routing in urban areas," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 242-265.
    6. Tricoire, Fabien & Parragh, Sophie N., 2017. "Investing in logistics facilities today to reduce routing emissions tomorrow," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 56-67.
    7. Yu, Yang & Wang, Sihan & Wang, Junwei & Huang, Min, 2019. "A branch-and-price algorithm for the heterogeneous fleet green vehicle routing problem with time windows," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 511-527.
    8. Ali Heidari & Din Mohammad Imani & Mohammad Khalilzadeh & Mahdieh Sarbazvatan, 2023. "Green two-echelon closed and open location-routing problem: application of NSGA-II and MOGWO metaheuristic approaches," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 9163-9199, September.
    9. Feiyue Qiu & Guodao Zhang & Ping-Kuo Chen & Cheng Wang & Yi Pan & Xin Sheng & Dewei Kong, 2020. "A Novel Multi-Objective Model for the Cold Chain Logistics Considering Multiple Effects," Sustainability, MDPI, vol. 12(19), pages 1-28, September.
    10. Stellingwerf, Helena M. & Groeneveld, Leendert H.C. & Laporte, Gilbert & Kanellopoulos, Argyris & Bloemhof, Jacqueline M. & Behdani, Behzad, 2021. "The quality-driven vehicle routing problem: Model and application to a case of cooperative logistics," International Journal of Production Economics, Elsevier, vol. 231(C).
    11. Turkensteen, Marcel, 2017. "The accuracy of carbon emission and fuel consumption computations in green vehicle routing," European Journal of Operational Research, Elsevier, vol. 262(2), pages 647-659.
    12. Soysal, Mehmet & Koç, Çağrı & Çimen, Mustafa & İbiş, Merve, 2023. "Managing returnable transport items in a vendor managed inventory system," Socio-Economic Planning Sciences, Elsevier, vol. 86(C).
    13. Pelletier, Samuel & Jabali, Ola & Laporte, Gilbert & Veneroni, Marco, 2017. "Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 158-187.
    14. Longlong Leng & Jingling Zhang & Chunmiao Zhang & Yanwei Zhao & Wanliang Wang & Gongfa Li, 2020. "A novel bi-objective model of cold chain logistics considering location-routing decision and environmental effects," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-29, April.
    15. Emna Marrekchi & Walid Besbes & Diala Dhouib & Emrah Demir, 2021. "A review of recent advances in the operations research literature on the green routing problem and its variants," Annals of Operations Research, Springer, vol. 304(1), pages 529-574, September.
    16. Huang, Yixiao & Zhao, Lei & Van Woensel, Tom & Gross, Jean-Philippe, 2017. "Time-dependent vehicle routing problem with path flexibility," Transportation Research Part B: Methodological, Elsevier, vol. 95(C), pages 169-195.
    17. Koç, Çağrı & Bektaş, Tolga & Jabali, Ola & Laporte, Gilbert, 2016. "A comparison of three idling options in long-haul truck scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 631-647.
    18. Zhang, Shuai & Gajpal, Yuvraj & Appadoo, S.S. & Abdulkader, M.M.S., 2018. "Electric vehicle routing problem with recharging stations for minimizing energy consumption," International Journal of Production Economics, Elsevier, vol. 203(C), pages 404-413.
    19. Dukkanci, Okan & Peker, Meltem & Kara, Bahar Y., 2019. "Green hub location problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 125(C), pages 116-139.
    20. Cao, Cejun & Liu, Yang & Tang, Ou & Gao, Xuehong, 2021. "A fuzzy bi-level optimization model for multi-period post-disaster relief distribution in sustainable humanitarian supply chains," International Journal of Production Economics, Elsevier, vol. 235(C).

    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:jmathe:v:9:y:2021:i:18:p:2325-:d:639022. 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.