IDEAS home Printed from https://ideas.repec.org/p/ant/wpaper/2012016.html
   My bibliography  Save this paper

Optimisation of water distribution network design: a critical review

Author

Listed:
  • DE CORTE, Annelies
  • SÖRENSEN, Kenneth

Abstract

This paper surveys the literature on the optimisation of water distribution network design. The water distribution network design (WDND) optimisation problem entails finding the type and diameter of each pipe in the network so that the total cost of the network is minimised without violating any hydraulic constraints. This is a difficult combinatorial optimisation problem, in which decision variables are discrete and both cost function and constraints are non-linear. Over the past 30 years, a large number of methods, especially in the field of (meta)heuristics, have been developed to solve this problem, most of which obtain good results on the available benchmark networks. In addition to outlining the basic features of each method, a detailed computational comparison is presented. The need for an adequate set of benchmark instances and the desirable properties of an instance set generator, are discussed. The paper concludes by pointing out some issues with the current state of the art in this domain and presents some suggestions for future research in this domain.

Suggested Citation

  • DE CORTE, Annelies & SÖRENSEN, Kenneth, 2012. "Optimisation of water distribution network design: a critical review," Working Papers 2012016, University of Antwerp, Faculty of Business and Economics.
  • Handle: RePEc:ant:wpaper:2012016
    as

    Download full text from publisher

    File URL: https://repository.uantwerpen.be/docman/irua/82324c/8ceb0df1.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Reuven Rubinstein, 1999. "The Cross-Entropy Method for Combinatorial and Continuous Optimization," Methodology and Computing in Applied Probability, Springer, vol. 1(2), pages 127-190, September.
    3. Fred Glover, 1989. "Tabu Search---Part I," INFORMS Journal on Computing, INFORMS, vol. 1(3), pages 190-206, August.
    4. Olli Bräysy & Michel Gendreau, 2005. "Vehicle Routing Problem with Time Windows, Part II: Metaheuristics," Transportation Science, INFORMS, vol. 39(1), pages 119-139, February.
    5. da Conceicao Cunha, Maria & Ribeiro, Luisa, 2004. "Tabu search algorithms for water network optimization," European Journal of Operational Research, Elsevier, vol. 157(3), pages 746-758, September.
    6. Szeto, W.Y. & Wu, Yongzhong & Ho, Sin C., 2011. "An artificial bee colony algorithm for the capacitated vehicle routing problem," European Journal of Operational Research, Elsevier, vol. 215(1), pages 126-135, November.
    7. J. Reca & J. Martínez & C. Gil & R. Baños, 2008. "Application of Several Meta-Heuristic Techniques to the Optimization of Real Looped Water Distribution Networks," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 22(10), pages 1367-1379, October.
    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. De Corte, Annelies & Sörensen, Kenneth, 2013. "Optimisation of gravity-fed water distribution network design: A critical review," European Journal of Operational Research, Elsevier, vol. 228(1), pages 1-10.
    2. Zhang, Ruiyou & Yun, Won Young & Moon, Il Kyeong, 2011. "Modeling and optimization of a container drayage problem with resource constraints," International Journal of Production Economics, Elsevier, vol. 133(1), pages 351-359, September.
    3. Gmira, Maha & Gendreau, Michel & Lodi, Andrea & Potvin, Jean-Yves, 2021. "Tabu search for the time-dependent vehicle routing problem with time windows on a road network," European Journal of Operational Research, Elsevier, vol. 288(1), pages 129-140.
    4. Ma, Hong & Cheang, Brenda & Lim, Andrew & Zhang, Lei & Zhu, Yi, 2012. "An investigation into the vehicle routing problem with time windows and link capacity constraints," Omega, Elsevier, vol. 40(3), pages 336-347.
    5. 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.
    6. Tai-Yu Ma, 2011. "A cross entropy multiagent learning algorithm for solving vehicle routing problems with time windows," Post-Print halshs-00592118, HAL.
    7. Lai, David S.W. & Caliskan Demirag, Ozgun & Leung, Janny M.Y., 2016. "A tabu search heuristic for the heterogeneous vehicle routing problem on a multigraph," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 86(C), pages 32-52.
    8. Asbach, Lasse & Dorndorf, Ulrich & Pesch, Erwin, 2009. "Analysis, modeling and solution of the concrete delivery problem," European Journal of Operational Research, Elsevier, vol. 193(3), pages 820-835, March.
    9. Chen, Qingfeng & Li, Kunpeng & Liu, Zhixue, 2014. "Model and algorithm for an unpaired pickup and delivery vehicle routing problem with split loads," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 69(C), pages 218-235.
    10. Fröhlich von Elmbach, Alexander & Scholl, Armin & Walter, Rico, 2019. "Minimizing the maximal ergonomic burden in intra-hospital patient transportation," European Journal of Operational Research, Elsevier, vol. 276(3), pages 840-854.
    11. 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.
    12. Annelies De Corte & Kenneth Sörensen, 2014. "HydroGen: an Artificial Water Distribution Network Generator," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 28(2), pages 333-350, January.
    13. Schmid, Verena & Doerner, Karl F. & Laporte, Gilbert, 2013. "Rich routing problems arising in supply chain management," European Journal of Operational Research, Elsevier, vol. 224(3), pages 435-448.
    14. Gerhard Hiermann & Matthias Prandtstetter & Andrea Rendl & Jakob Puchinger & Günther Raidl, 2015. "Metaheuristics for solving a multimodal home-healthcare scheduling problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 23(1), pages 89-113, March.
    15. Theys, Christophe & Bräysy, Olli & Dullaert, Wout & Raa, Birger, 2010. "Using a TSP heuristic for routing order pickers in warehouses," European Journal of Operational Research, Elsevier, vol. 200(3), pages 755-763, February.
    16. 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).
    17. Hideki Hashimoto & Mutsunori Yagiura & Shinji Imahori & Toshihide Ibaraki, 2013. "Recent progress of local search in handling the time window constraints of the vehicle routing problem," Annals of Operations Research, Springer, vol. 204(1), pages 171-187, April.
    18. Chiang, Wen-Chyuan & Russell, Robert & Xu, Xiaojing & Zepeda, David, 2009. "A simulation/metaheuristic approach to newspaper production and distribution supply chain problems," International Journal of Production Economics, Elsevier, vol. 121(2), pages 752-767, October.
    19. Maaike Hoogeboom & Wout Dullaert & David Lai & Daniele Vigo, 2020. "Efficient Neighborhood Evaluations for the Vehicle Routing Problem with Multiple Time Windows," Transportation Science, INFORMS, vol. 54(2), pages 400-416, March.
    20. Ullrich, Christian A., 2013. "Integrated machine scheduling and vehicle routing with time windows," European Journal of Operational Research, Elsevier, vol. 227(1), pages 152-165.

    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:ant:wpaper:2012016. 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: Joeri Nys (email available below). General contact details of provider: https://edirc.repec.org/data/ftufsbe.html .

    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.