IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v146y2013i1p313-324.html
   My bibliography  Save this article

Optimal algorithm for the demand routing problem in multicommodity flow distribution networks with diversification constraints and concave costs

Author

Listed:
  • Cortés, Pablo
  • Muñuzuri, Jesús
  • Guadix, José
  • Onieva, Luis

Abstract

Distribution problems are of high relevance within the supply chain system. In real life situations various different commodities may flow in the distribution process. Furthermore, the connection between production and demand centres makes use of complex mesh networks that can include diversification constraints to avoid overcharged paths. In addition, the consideration in certain situations of economies of scale gives rise to non-linear cost functions that make it difficult to deal with an optimal routing scheme. This problem is well represented by the multicommodity flow distribution networks with diversification constraints and concave costs (MFDCC) problem. Here we present an optimal algorithm based on the Kuhn–Tucker optimality conditions of the problem and capable of supplying optimal distribution routes in such complex networks. The algorithm follows an iterative procedure. Each iteration constructive solutions are checked with respect to the Kuhn–Tucker optimality conditions. Solutions consider a set of paths transporting all the demand allowed by its diversification constraint (saturated paths), a set of empty paths, and an indicator path transporting the remaining demand to satisfy the demand equation. The algorithm reduces the total cost in the network in a monotonic sequence to the optimum. The algorithm was tested in a trial library and the optimum was reached for all the instances. The algorithm showed a major dependency with respect to the number of nodes and arcs of the graph, as well as the density of arcs in the graph.

Suggested Citation

  • Cortés, Pablo & Muñuzuri, Jesús & Guadix, José & Onieva, Luis, 2013. "Optimal algorithm for the demand routing problem in multicommodity flow distribution networks with diversification constraints and concave costs," International Journal of Production Economics, Elsevier, vol. 146(1), pages 313-324.
  • Handle: RePEc:eee:proeco:v:146:y:2013:i:1:p:313-324
    DOI: 10.1016/j.ijpe.2013.07.016
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527313003289
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2013.07.016?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. Ubeda, S. & Arcelus, F.J. & Faulin, J., 2011. "Green logistics at Eroski: A case study," International Journal of Production Economics, Elsevier, vol. 131(1), pages 44-51, May.
    2. Larry J. LeBlanc, 1976. "Global Solutions for a Nonconvex Nonconcave Rail Network Model," Management Science, INFORMS, vol. 23(2), pages 131-139, October.
    3. Tsao, Yu-Chung & Sheen, Gwo-Ji, 2012. "A multi-item supply chain with credit periods and weight freight cost discounts," International Journal of Production Economics, Elsevier, vol. 135(1), pages 106-115.
    4. Kengpol, Athakorn & Meethom, Warapoj & Tuominen, Markku, 2012. "The development of a decision support system in multimodal transportation routing within Greater Mekong sub-region countries," International Journal of Production Economics, Elsevier, vol. 140(2), pages 691-701.
    5. Larsson, Torbjorn & Migdalas, Athanasios & Ronnqvist, Mikael, 1994. "A Lagrangean heuristic for the capacitated concave minimum cost network flow problem," European Journal of Operational Research, Elsevier, vol. 78(1), pages 116-129, October.
    6. Pablo Cortes & Jesus Muñuzuri & Luis Onieva & Juan Larrañeta & Juan M. Vozmediano & Jose C. Alarcon, 2006. "Andalucía Assesses the Investment Needed to Deploy a Fiber-Optic Network," Interfaces, INFORMS, vol. 36(2), pages 105-117, April.
    7. Willard I. Zangwill, 1968. "Minimum Concave Cost Flows in Certain Networks," Management Science, INFORMS, vol. 14(7), pages 429-450, March.
    8. Michael Florian & Morton Klein, 1971. "Deterministic Production Planning with Concave Costs and Capacity Constraints," Management Science, INFORMS, vol. 18(1), pages 12-20, September.
    9. Yan, Shangyao & Luo, So-Chang, 1999. "Probabilistic local search algorithms for concave cost transportation network problems," European Journal of Operational Research, Elsevier, vol. 117(3), pages 511-521, September.
    10. G Zhou & M Gen, 2003. "A genetic algorithm approach on tree-like telecommunication network design problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(3), pages 248-254, March.
    11. F Altiparmak & I Karaoglan, 2008. "An adaptive tabu-simulated annealing for concave cost transportation problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 331-341, March.
    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. Shiyuan Zheng & Rudy R. Negenborn, 2017. "Terminal investment timing decisions in a competitive setting with uncertainty using a real option approach," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(3), pages 392-411, April.
    2. Khodakaram Salimifard & Sara Bigharaz, 2022. "The multicommodity network flow problem: state of the art classification, applications, and solution methods," Operational Research, Springer, vol. 22(1), pages 1-47, March.

    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. F Altiparmak & I Karaoglan, 2008. "An adaptive tabu-simulated annealing for concave cost transportation problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(3), pages 331-341, March.
    2. Yan, Shangyao & Luo, So-Chang, 1999. "Probabilistic local search algorithms for concave cost transportation network problems," European Journal of Operational Research, Elsevier, vol. 117(3), pages 511-521, September.
    3. Karla E. Bourland & Candace Arai Yano, 1996. "Lot sizing when yields increase during the production run," Naval Research Logistics (NRL), John Wiley & Sons, vol. 43(8), pages 1035-1047, December.
    4. Chung‐Lun Li & Jinwen Ou & Vernon N. Hsu, 2012. "Dynamic lot sizing with all‐units discount and resales," Naval Research Logistics (NRL), John Wiley & Sons, vol. 59(3‐4), pages 230-243, April.
    5. Hark-Chin Hwang & Hyun-Soo Ahn & Philip Kaminsky, 2013. "Basis Paths and a Polynomial Algorithm for the Multistage Production-Capacitated Lot-Sizing Problem," Operations Research, INFORMS, vol. 61(2), pages 469-482, April.
    6. Hwang, Hark-Chin & Kang, Jangha, 2020. "The two-level lot-sizing problem with outbound shipment," Omega, Elsevier, vol. 90(C).
    7. Önal, Mehmet & Romeijn, H.Edwin & Sapra, Amar & van den Heuvel, Wilco, 2015. "The economic lot-sizing problem with perishable items and consumption order preference," European Journal of Operational Research, Elsevier, vol. 244(3), pages 881-891.
    8. Hwang, Hark-Chin & Jaruphongsa, Wikrom, 2008. "Dynamic lot-sizing model for major and minor demands," European Journal of Operational Research, Elsevier, vol. 184(2), pages 711-724, January.
    9. Wolsey, Laurence A., 1995. "Progress with single-item lot-sizing," European Journal of Operational Research, Elsevier, vol. 86(3), pages 395-401, November.
    10. Guan, Yongpei & Liu, Tieming, 2010. "Stochastic lot-sizing problem with inventory-bounds and constant order-capacities," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1398-1409, December.
    11. Vasilios I. Manousiouthakis & Neil Thomas & Ahmad M. Justanieah, 2011. "On a Finite Branch and Bound Algorithm for the Global Minimization of a Concave Power Law Over a Polytope," Journal of Optimization Theory and Applications, Springer, vol. 151(1), pages 121-134, October.
    12. Eksioglu, Sandra Duni, 2009. "A primal-dual algorithm for the economic lot-sizing problem with multi-mode replenishment," European Journal of Operational Research, Elsevier, vol. 197(1), pages 93-101, August.
    13. Liu, X. & Tu, Yl., 2008. "Production planning with limited inventory capacity and allowed stockout," International Journal of Production Economics, Elsevier, vol. 111(1), pages 180-191, January.
    14. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria & van den Heuvel, Wilco, 2020. "A single-item lot-sizing problem with a by-product and inventory capacities," European Journal of Operational Research, Elsevier, vol. 287(3), pages 844-855.
    15. Mathieu Van Vyve, 2007. "Algorithms for Single-Item Lot-Sizing Problems with Constant Batch Size," Mathematics of Operations Research, INFORMS, vol. 32(3), pages 594-613, August.
    16. Kumar, V.N.S.A. & Kumar, V. & Brady, M. & Garza-Reyes, Jose Arturo & Simpson, M., 2017. "Resolving forward-reverse logistics multi-period model using evolutionary algorithms," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 458-469.
    17. Mutlu, Fatih & Çetinkaya, Sıla, 2020. "Supplier–carrier–buyer channels: Contractual pricing for a carrier serving a supplier–buyer partnership," International Journal of Production Economics, Elsevier, vol. 230(C).
    18. Ming Zhao & Minjiao Zhang, 2020. "Multiechelon Lot Sizing: New Complexities and Inequalities," Operations Research, INFORMS, vol. 68(2), pages 534-551, March.
    19. Li Chen & Hau L. Lee, 2012. "Bullwhip Effect Measurement and Its Implications," Operations Research, INFORMS, vol. 60(4), pages 771-784, August.
    20. Stan van Hoesel & H. Edwin Romeijn & Dolores Romero Morales & Albert P. M. Wagelmans, 2005. "Integrated Lot Sizing in Serial Supply Chains with Production Capacities," Management Science, INFORMS, vol. 51(11), pages 1706-1719, November.

    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:proeco:v:146:y:2013:i:1:p:313-324. 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/locate/ijpe .

    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.