IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v291y2020i1d10.1007_s10479-018-3071-0.html
   My bibliography  Save this article

Cold chain distribution: How to deal with node and arc time windows?

Author

Listed:
  • Yi Zhang

    (Beijing Wuzi University)

  • Guowei Hua

    (Beijing Jiaotong University)

  • T. C. E. Cheng

    (The Hong Kong Polytechnic University)

  • Juliang Zhang

    (Beijing Jiaotong University)

Abstract

Commonly encountered in cold chain logistics, third-party distribution firms are required to deliver temperature-sensitive food products to various retailers with two kinds of time-window constraints: (1) the delivery service must begin within the time windows imposed by the retailers (called node time windows) and (2) each vehicle route is available only in a predefined time interval prescribed by the government (called arc time windows). We study the effects of the retailer time window type (i.e., density of the node time-window constraints) and other cost-related factors on a distribution firm’s legitimacy choice (i.e., the firm chooses to either comply with or violate the governmental time-window policy), food quality, and pollutant emissions in the urban environment. We model the problem as an intractable vehicle routing problem with node and arc time windows and develop a genetic algorithm to tackle it. We conduct a case study to generate the managerial insights on dealing with time windows. We find that the governmental time windows will increase the distribution cost. The governmental time windows has a negative effect on pollutant emissions while showing a positive effect on food safety. Given governmental time windows, a higher demand for node time windows will result in more governmental time-window violations or lower vehicle load factor, which depends on the vehicle fixed cost, fuel price, and government penalty.

Suggested Citation

  • Yi Zhang & Guowei Hua & T. C. E. Cheng & Juliang Zhang, 2020. "Cold chain distribution: How to deal with node and arc time windows?," Annals of Operations Research, Springer, vol. 291(1), pages 1127-1151, August.
    • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-018-3071-0
    DOI: 10.1007/s10479-018-3071-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-018-3071-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-018-3071-0?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. Thibaut Vidal & Teodor Gabriel Crainic & Michel Gendreau & Nadia Lahrichi & Walter Rei, 2012. "A Hybrid Genetic Algorithm for Multidepot and Periodic Vehicle Routing Problems," Operations Research, INFORMS, vol. 60(3), pages 611-624, June.
    2. Eric Prescott-Gagnon & Guy Desaulniers & Michael Drexl & Louis-Martin Rousseau, 2010. "European Driver Rules in Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 44(4), pages 455-473, November.
    3. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    4. Çetinkaya, Cihan & Karaoglan, Ismail & Gökçen, Hadi, 2013. "Two-stage vehicle routing problem with arc time windows: A mixed integer programming formulation and a heuristic approach," European Journal of Operational Research, Elsevier, vol. 230(3), pages 539-550.
    5. Govindan, K. & Jafarian, A. & Khodaverdi, R. & Devika, K., 2014. "Two-echelon multiple-vehicle location–routing problem with time windows for optimization of sustainable supply chain network of perishable food," International Journal of Production Economics, Elsevier, vol. 152(C), pages 9-28.
    6. Songyi Wang & Fengming Tao & Yuhe Shi & Haolin Wen, 2017. "Optimization of Vehicle Routing Problem with Time Windows for Cold Chain Logistics Based on Carbon Tax," Sustainability, MDPI, vol. 9(5), pages 1-23, April.
    7. Amorim, P. & Belo-Filho, M.A.F. & Toledo, F.M.B. & Almeder, C. & Almada-Lobo, B., 2013. "Lot sizing versus batching in the production and distribution planning of perishable goods," International Journal of Production Economics, Elsevier, vol. 146(1), pages 208-218.
    8. Quak, H.J. & de Koster, M.B.M., 2006. "Urban Distribution: The Impacts of Different Governmental Time-Window Schemes," ERIM Report Series Research in Management ERS-2006-053-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.
    9. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part I: Route Construction and Local Search Algorithms," Transportation Science, INFORMS, vol. 39(1), pages 104-118, February.
    10. Liu, Ran & Xie, Xiaolan & Augusto, Vincent & Rodriguez, Carlos, 2013. "Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care," European Journal of Operational Research, Elsevier, vol. 230(3), pages 475-486.
    11. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    12. H. J. (Hans) Quak & M. (René) B. M. de Koster, 2009. "Delivering Goods in Urban Areas: How to Deal with Urban Policy Restrictions and the Environment," Transportation Science, INFORMS, vol. 43(2), pages 211-227, May.
    13. Asvin Goel, 2009. "Vehicle Scheduling and Routing with Drivers' Working Hours," Transportation Science, INFORMS, vol. 43(1), pages 17-26, February.
    14. Vincent F. Yu & Parida Jewpanya & Voratas Kachitvichyanukul, 2016. "Particle swarm optimization for the multi-period cross-docking distribution problem with time windows," International Journal of Production Research, Taylor & Francis Journals, vol. 54(2), pages 509-525, January.
    15. Liang-Liang Fu & Mohamed Ali Aloulou & Chefi Triki, 2017. "Integrated production scheduling and vehicle routing problem with job splitting and delivery time windows," International Journal of Production Research, Taylor & Francis Journals, vol. 55(20), pages 5942-5957, October.
    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. Lin Li & Qiangwei Zhang & Tie Zhang & Yanbiao Zou & Xing Zhao, 2023. "Optimum Route and Transport Mode Selection of Multimodal Transport with Time Window under Uncertain Conditions," Mathematics, MDPI, vol. 11(14), pages 1-25, July.
    2. Shenjun Zhu & Hongming Fu & Yanhui Li, 2021. "Optimization Research on Vehicle Routing for Fresh Agricultural Products Based on the Investment of Freshness-Keeping Cost in the Distribution Process," Sustainability, MDPI, vol. 13(14), pages 1-22, July.
    3. Francesco Ciardiello & Andrea Genovese & Shucheng Luo & Antonino Sgalambro, 2023. "A game-theoretic multi-stakeholder model for cost allocation in urban consolidation centres," Annals of Operations Research, Springer, vol. 324(1), pages 663-686, May.
    4. Benyamin Moghaddasi & Amir Salar Ghafari Majid & Zahra Mohammadnazari & Amir Aghsami & Masoud Rabbani, 2023. "A green routing-location problem in a cold chain logistics network design within the Balanced Score Card pillars in fuzzy environment," Journal of Combinatorial Optimization, Springer, vol. 45(5), pages 1-33, July.
    5. Hafiz Wasim Akram & Samreen Akhtar & Alam Ahmad & Imran Anwar & Mohammad Ali Bait Ali Sulaiman, 2023. "Developing a Conceptual Framework Model for Effective Perishable Food Cold-Supply-Chain Management Based on Structured Literature Review," Sustainability, MDPI, vol. 15(6), pages 1-28, March.
    6. Meiling He & Mei Yang & Xiaohui Wu & Jun Pu & Kazuhiro Izui, 2024. "Evaluating and Analyzing the Efficiency and Influencing Factors of Cold Chain Logistics in China’s Major Urban Agglomerations under Carbon Constraints," Sustainability, MDPI, vol. 16(5), pages 1-19, February.

    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. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2013. "Heuristics for multi-attribute vehicle routing problems: A survey and synthesis," European Journal of Operational Research, Elsevier, vol. 231(1), pages 1-21.
    2. Alcaraz, Juan J. & Caballero-Arnaldos, Luis & Vales-Alonso, Javier, 2019. "Rich vehicle routing problem with last-mile outsourcing decisions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 263-286.
    3. Nicolas Rincon-Garcia & Ben J. Waterson & Tom J. Cherrett, 2018. "Requirements from vehicle routing software: perspectives from literature, developers and the freight industry," Transport Reviews, Taylor & Francis Journals, vol. 38(1), pages 117-138, January.
    4. Lahyani, Rahma & Khemakhem, Mahdi & Semet, Frédéric, 2015. "Rich vehicle routing problems: From a taxonomy to a definition," European Journal of Operational Research, Elsevier, vol. 241(1), pages 1-14.
    5. Zajac, Sandra & Huber, Sandra, 2021. "Objectives and methods in multi-objective routing problems: a survey and classification scheme," European Journal of Operational Research, Elsevier, vol. 290(1), pages 1-25.
    6. Asvin Goel & Thibaut Vidal, 2014. "Hours of Service Regulations in Road Freight Transport: An Optimization-Based International Assessment," Transportation Science, INFORMS, vol. 48(3), pages 391-412, August.
    7. Wang, Zheng, 2018. "Delivering meals for multiple suppliers: Exclusive or sharing logistics service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 118(C), pages 496-512.
    8. Ostermeier, Manuel, 2024. "The supply of convenience stores: Challenges of short-distance routing within the constraints of working time regulations," European Journal of Operational Research, Elsevier, vol. 314(3), pages 997-1012.
    9. Liu, Ran & Xie, Xiaolan & Garaix, Thierry, 2014. "Hybridization of tabu search with feasible and infeasible local searches for periodic home health care logistics," Omega, Elsevier, vol. 47(C), pages 17-32.
    10. Eric Prescott-Gagnon & Guy Desaulniers & Michael Drexl & Louis-Martin Rousseau, 2010. "European Driver Rules in Vehicle Routing with Time Windows," Transportation Science, INFORMS, vol. 44(4), pages 455-473, November.
    11. Nguyen, Phuong Khanh & Crainic, Teodor Gabriel & Toulouse, Michel, 2013. "A tabu search for Time-dependent Multi-zone Multi-trip Vehicle Routing Problem with Time Windows," European Journal of Operational Research, Elsevier, vol. 231(1), pages 43-56.
    12. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    13. Mohamed Cissé & Semih Yalçindag & Yannick Kergosien & Evren Sahin & Christophe Lenté & Andrea Matta, 2017. "OR problems related to Home Health Care: A review of relevant routing and scheduling problems," Post-Print hal-01736714, HAL.
    14. Schneider, Michael & Schwahn, Fabian & Vigo, Daniele, 2017. "Designing granular solution methods for routing problems with time windows," European Journal of Operational Research, Elsevier, vol. 263(2), pages 493-509.
    15. Vidal, Thibaut & Crainic, Teodor Gabriel & Gendreau, Michel & Prins, Christian, 2014. "A unified solution framework for multi-attribute vehicle routing problems," European Journal of Operational Research, Elsevier, vol. 234(3), pages 658-673.
    16. Qi, Mingyao & Lin, Wei-Hua & Li, Nan & Miao, Lixin, 2012. "A spatiotemporal partitioning approach for large-scale vehicle routing problems with time windows," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 248-257.
    17. Zhiping Zuo & Yanhui Li & Jing Fu & Jianlin Wu, 2019. "Human Resource Scheduling Model and Algorithm with Time Windows and Multi-Skill Constraints," Mathematics, MDPI, vol. 7(7), pages 1-18, July.
    18. Baals, Julian & Emde, Simon & Turkensteen, Marcel, 2023. "Minimizing earliness-tardiness costs in supplier networks—A just-in-time truck routing problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 707-741.
    19. Subramanyam, Anirudh & Wang, Akang & Gounaris, Chrysanthos E., 2018. "A scenario decomposition algorithm for strategic time window assignment vehicle routing problems," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 296-317.
    20. Mohammad Torkjazi & Nathan Huynh, 2019. "Effectiveness of Dynamic Insertion Scheduling Strategy for Demand-Responsive Paratransit Vehicles Using Agent-Based Simulation," Sustainability, MDPI, vol. 11(19), pages 1-12, September.

    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:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-018-3071-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.