IDEAS home Printed from https://ideas.repec.org/a/bla/presci/v87y2008i4p605-621.html
   My bibliography  Save this article

Supply chain network equilibrium problem with capacity constraints

Author

Listed:
  • Huey‐Kuo Chen
  • Huey‐Wen Chou

Abstract

The supply chain network equilibrium problem with capacity constraints (SCNE‐C) is an extension of the supply chain network equilibrium problem (SCNE), which also takes into account capacity constraints which refer to the maximum production capacity for a manufacturer or the maximum storage/display space for a retailer. Due to inherent link interactions in the demand functions and cost functions, the SCNE‐C problem is formulated as a mathematical model using the variational inequality (VI) approach. This VI model is characterised by the so‐called Wardrop second principle (in terms of the ‘generalised’ route cost). To solve the model, a path‐based four‐loop nested diagonalisation method, along with a supernetwork representation, is proposed and demonstrated with a few numerical examples. The obtained results fully comply with the Wardrop second principle at both retailer sector and demand markets and can provide useful route information of the product. In addition, the stricter the capacity constraints imposed, the lower the quantity demanded will be, and provided at a higher product price. The concepts developed in this paper can be extended into many other spatial price equilibrium problems. Resumen El problema de equilibrio en la red de la cadena de abastecimiento con restricciones de capacidad (SCNE‐C) es una ampliación del problema de equilibrio en la red de la cadena de abastecimiento, que además tiene en cuenta restricciones de capacidad relacionadas con la máxima capacidad de producción para un fabricante o el espacio máximo de almacenamiento/muestra al público para un comerciante al por menor. Debido a las interacciones inherentes entre vínculos en las funciones de demanda y de costos, formulamos el problema de SCNE‐C como un modelo matemático utilizando el enfoque de desigualdad variacional (VI). Este modelo VI se caracteriza por el así llamado segundo principio de Wardrop (en términos de costo de recorrido ‘generalizado’). Para resolver el modelo se propone un método de diagonalización anidado de cuatro bucles basado en la ruta, junto con una representación de red extendida (supernetwork), y se demuestra con algunos ejemplos numéricos. Los resultados obtenidos cumplen totalmente con el segundo principio de Wardrop tanto para el sector de minoristas como para las demandas del mercado y pueden proporcionar información de ruta útil del producto. Además, cuanto más estrictas sean las restricciones de capacidad impuestas, menor será la cantidad demandada del producto, y se ofrecerá con un precio mayor. Los conceptos desarrollados en este artículo pueden aplicarse a muchos otros problemas espaciales de equilibrio de precios.

Suggested Citation

  • Huey‐Kuo Chen & Huey‐Wen Chou, 2008. "Supply chain network equilibrium problem with capacity constraints," Papers in Regional Science, Wiley Blackwell, vol. 87(4), pages 605-621, November.
  • Handle: RePEc:bla:presci:v:87:y:2008:i:4:p:605-621
    DOI: 10.1111/j.1435-5957.2008.00174.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1435-5957.2008.00174.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1435-5957.2008.00174.x?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
    ---><---

    References listed on IDEAS

    as
    1. Jayakrishnan, R. & Tsai, Wei T. & Prashker, Joseph N. & Rajadhyaksha, Subodh, 1994. "A Faster Path-Based Algorithm for Traffic Assignment," University of California Transportation Center, Working Papers qt2hf4541x, University of California Transportation Center.
    2. Nagurney, Anna & Dong, June & Zhang, Ding, 2002. "A supply chain network equilibrium model," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 38(5), pages 281-303, September.
    3. Larsson, Torbjörn & Patriksson, Michael, 1995. "An augmented lagrangean dual algorithm for link capacity side constrained traffic assignment problems," Transportation Research Part B: Methodological, Elsevier, vol. 29(6), pages 433-455, December.
    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. Hamdouch, Younes & Ghoudi, Kilani, 2020. "A Supply Chain Equilibrium Model with General Price-Dependent Demand," Operations Research Perspectives, Elsevier, vol. 7(C).
    2. Hu, Xiaowei & Li, Peng, 2022. "Relief and stimulus in a cross-sector multi-product scarce resource supply chain network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).

    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. Wu, Xin & Nie, Lei & Xu, Meng & Yan, Fei, 2018. "A perishable food supply chain problem considering demand uncertainty and time deadline constraints: Modeling and application to a high-speed railway catering service," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 186-209.
    2. Xu, Zhandong & Xie, Jun & Liu, Xiaobo & Nie, Yu (Marco), 2020. "Hyperpath-based algorithms for the transit equilibrium assignment problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 143(C).
    3. Nie, Yu (Marco), 2010. "A class of bush-based algorithms for the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 44(1), pages 73-89, January.
    4. Zugang Liu & Anna Nagurney, 2009. "An integrated electric power supply chain and fuel market network framework: Theoretical modeling with empirical analysis for New England," Naval Research Logistics (NRL), John Wiley & Sons, vol. 56(7), pages 600-624, October.
    5. Abdelfettah Laouzai & Rachid Ouafi, 2022. "A prediction model for atmospheric pollution reduction from urban traffic," Environment and Planning B, , vol. 49(2), pages 566-584, February.
    6. Chou, Chang-Chi & Chiang, Wen-Chu & Chen, Albert Y., 2022. "Emergency medical response in mass casualty incidents considering the traffic congestions in proximity on-site and hospital delays," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    7. Seungkyu Ryu & Anthony Chen & Xiangdong Xu & Keechoo Choi, 2014. "A Dual Approach for Solving the Combined Distribution and Assignment Problem with Link Capacity Constraints," Networks and Spatial Economics, Springer, vol. 14(2), pages 245-270, June.
    8. Nagurney, Anna & Saberi, Sara & Shukla, Shivani & Floden, Jonas, 2015. "Supply chain network competition in price and quality with multiple manufacturers and freight service providers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 77(C), pages 248-267.
    9. Yang, Yuxiang & Goodarzi, Shadi & Jabbarzadeh, Armin & Fahimnia, Behnam, 2022. "In-house production and outsourcing under different emissions reduction regulations: An equilibrium decision model for global supply chains," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
    10. Palsule-Desai, Omkar D., 2015. "Cooperatives for fruits and vegetables in emerging countries: Rationalization and impact of decentralization," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 114-140.
    11. Shen, Wei & Wynter, Laura, 2012. "A new one-level convex optimization approach for estimating origin–destination demand," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1535-1555.
    12. Zheng, Hong & Peeta, Srinivas, 2014. "Cost scaling based successive approximation algorithm for the traffic assignment problem," Transportation Research Part B: Methodological, Elsevier, vol. 68(C), pages 17-30.
    13. Wang, Jian & He, Xiaozheng & Peeta, Srinivas & Wang, Wei, 2022. "Globally convergent line search algorithm with Euler-based step size-determination method for continuous network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 119-144.
    14. Huang, Hai-Jun & Xu, Gang, 1998. "Aggregate scheduling and network solving of multi-stage and multi-item manufacturing systems," European Journal of Operational Research, Elsevier, vol. 105(1), pages 52-65, February.
    15. Du, Muqing & Tan, Heqing & Chen, Anthony, 2021. "A faster path-based algorithm with Barzilai-Borwein step size for solving stochastic traffic equilibrium models," European Journal of Operational Research, Elsevier, vol. 290(3), pages 982-999.
    16. Nagurney, Anna, 2021. "Supply chain game theory network modeling under labor constraints: Applications to the Covid-19 pandemic," European Journal of Operational Research, Elsevier, vol. 293(3), pages 880-891.
    17. Babak Javani & Abbas Babazadeh, 2020. "Path-Based Dynamic User Equilibrium Model with Applications to Strategic Transportation Planning," Networks and Spatial Economics, Springer, vol. 20(2), pages 329-366, June.
    18. Xin Lin & Chris M. J. Tampère & Stef Proost, 2020. "Optimizing Traffic System Performance with Environmental Constraints: Tolls and/or Additional Delays," Networks and Spatial Economics, Springer, vol. 20(1), pages 137-177, March.
    19. Bagloee, Saeed Asadi & Sarvi, Majid & Wolshon, Brian & Dixit, Vinayak, 2017. "Identifying critical disruption scenarios and a global robustness index tailored to real life road networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 98(C), pages 60-81.
    20. Tatsuya Hirano & Yasushi Narushima, 2019. "Robust Supply Chain Network Equilibrium Model," Transportation Science, INFORMS, vol. 53(4), pages 1196-1212, July.

    More about this item

    Statistics

    Access and download statistics

    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:bla:presci:v:87:y:2008:i:4:p:605-621. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=1056-8190 .

    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.