IDEAS home Printed from https://ideas.repec.org/a/wly/navres/v67y2020i6p420-437.html
   My bibliography  Save this article

A guarantee rate optimization model for wastewater treatment system design under uncertainty

Author

Listed:
  • Kena Zhao
  • Tsan Sheng Adam Ng
  • Xiao Liu

Abstract

We consider a design problem for wastewater treatment systems that considers uncertainty in pollutant concentration levels at water sources. The goal is to optimize the selection of treatment technologies and pipeline connections, so that treated wastewater can achieve specified effluents discharge limits as well as possible. We propose a new two‐stage model to optimize a set of guarantee levels, that is, the maximum concentration level of source pollutants for which treated wastewater can be compliant with discharge limits. In the first stage, treatment technologies and pipeline connections are selected. In the second stage, when pollutant concentration levels are revealed, wastewater distribution and mixing are determined. A key attractiveness of the proposed guarantee rate optimization model is that it can be simplified into a single‐stage mixed‐integer linear program. In our numerical experiments based on real‐world pollutants data, the guarantee rate model demonstrates its advantages in terms of computational efficiency, scalability and solution quality, compared with the standard probability maximization model. Finally, the methodology proposed in this paper can also be applied to other two‐stage problems under uncertainty with similar uncertainty characteristics.

Suggested Citation

  • Kena Zhao & Tsan Sheng Adam Ng & Xiao Liu, 2020. "A guarantee rate optimization model for wastewater treatment system design under uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(6), pages 420-437, September.
    • Handle: RePEc:wly:navres:v:67:y:2020:i:6:p:420-437
    DOI: 10.1002/nav.21921
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/nav.21921
    Download Restriction: no
    File URL: https://libkey.io/10.1002/nav.21921?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. Listes, Ovidiu & Dekker, Rommert, 2005. "A stochastic approach to a case study for product recovery network design," European Journal of Operational Research, Elsevier, vol. 160(1), pages 268-287, January.
    2. H. Frank, 1967. "Letter to the Editor—Optimum Locations on Graphs with Correlated Normal Demands," Operations Research, INFORMS, vol. 15(3), pages 552-557, June.
    3. John J. Jarvis & Ronald L. Rardin & V. E. Unger & Richard W. Moore & Charles C. Schimpeler, 1978. "Optimal Design of Regional Wastewater Systems: A Fixed-Charge Network Flow Model," Operations Research, INFORMS, vol. 26(4), pages 538-550, August.
    4. V. Balachandran & Suresh Jain, 1976. "Optimal Facility Location Under Random Demand With General Cost Structure," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 23(3), pages 421-436, September.
    5. A. Charnes & W. W. Cooper, 1959. "Chance-Constrained Programming," Management Science, INFORMS, vol. 6(1), pages 73-79, October.
    6. H. Frank, 1966. "Optimum Locations on a Graph with Probabilistic Demands," Operations Research, INFORMS, vol. 14(3), pages 409-421, June.
    7. Kovacs, LaszloBela & Boros, Endre & Inotay, Ference, 1986. "A two-stage approach for large-scale sewer systems design with application to the Lake Balaton resort area," European Journal of Operational Research, Elsevier, vol. 23(2), pages 169-178, February.
    8. Shiode, Shogo & Drezner, Zvi, 2003. "A competitive facility location problem on a tree network with stochastic weights," European Journal of Operational Research, Elsevier, vol. 149(1), pages 47-52, August.
    9. Shuming Wang & Tsan Sheng Ng & Manyu Wong, 2016. "Expansion planning for waste‐to‐energy systems using waste forecast prediction sets," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(1), pages 47-70, February.
    10. Bruce L. Golden & Christopher C. Skiscim, 1986. "Using simulated annealing to solve routing and location problems," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 33(2), pages 261-279, May.
    11. Oded Berman & Jiamin Wang & Zvi Drezner & George Wesolowsky, 2003. "A Probabilistic Minimax Location Problem on the Plane," Annals of Operations Research, Springer, vol. 122(1), pages 59-70, September.
    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. Khannoussi, Arwa & Meyer, Patrick & Chaubet, Aurore, 2023. "A multi-criteria decision aiding approach for upgrading public sewerage systems and its application to the city of Brest," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).

    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. Jiamin Wang, 2007. "The (beta)-Reliable Median on a Network with Discrete Probabilistic Demand Weights," Operations Research, INFORMS, vol. 55(5), pages 966-975, October.
    2. Farahani, Reza Zanjirani & Rezapour, Shabnam & Drezner, Tammy & Fallah, Samira, 2014. "Competitive supply chain network design: An overview of classifications, models, solution techniques and applications," Omega, Elsevier, vol. 45(C), pages 92-118.
    3. Igor Averbakh & Oded Berman, 2000. "Minmax Regret Median Location on a Network Under Uncertainty," INFORMS Journal on Computing, INFORMS, vol. 12(2), pages 104-110, May.
    4. Haifa Jammeli & Majdi Argoubi & Hatem Masri, 2021. "A Bi-objective stochastic programming model for the household waste collection and transportation problem: case of the city of Sousse," Operational Research, Springer, vol. 21(3), pages 1613-1639, September.
    5. David Kik & Matthias G. Wichmann & Thomas S. Spengler, 2023. "Small- or Medium-Sized Enterprise Uses Operations Research to Select and Develop its Headquarters Location," Interfaces, INFORMS, vol. 53(4), pages 312-331, July.
    6. George L. Vairaktarakis & Panagiotis Kouvelis, 1999. "Incorporation dynamic aspects and uncertainty in 1‐median location problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 46(2), pages 147-168, March.
    7. Pal, Raktim & Bose, Indranil, 2009. "An optimization based approach for deployment of roadway incident response vehicles with reliability constraints," European Journal of Operational Research, Elsevier, vol. 198(2), pages 452-463, October.
    8. Li, Na & Jiang, Yue & Zhang, Zhi-Hai, 2021. "A two-stage ambiguous stochastic program for electric vehicle charging station location problem with valet charging service," Transportation Research Part B: Methodological, Elsevier, vol. 153(C), pages 149-171.
    9. O Berman & J Wang, 2008. "The probabilistic 1-maximal covering problem on a network with discrete demand weights," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(10), pages 1398-1405, October.
    10. Igor Averbakh, 2005. "The Minmax Relative Regret Median Problem on Networks," INFORMS Journal on Computing, INFORMS, vol. 17(4), pages 451-461, November.
    11. Azarnoosh Kafi & Behrouz Daneshian & Mohsen Rostamy-Malkhalifeh, 2021. "Forecasting the confidence interval of efficiency in fuzzy DEA," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 31(1), pages 41-59.
    12. Sander Claeys & Marta Vanin & Frederik Geth & Geert Deconinck, 2021. "Applications of optimization models for electricity distribution networks," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(5), September.
    13. Scott, James & Ho, William & Dey, Prasanta K. & Talluri, Srinivas, 2015. "A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments," International Journal of Production Economics, Elsevier, vol. 166(C), pages 226-237.
    14. Yves SMEERS & Daniel TYTECA, 1980. "Optimisation Économique Et Fiabilité Des Réseaux Intercommunaux De Stations D'Épuration," Annals of Public and Cooperative Economics, Wiley Blackwell, vol. 51(1-2), pages 69-95, 01-06.
    15. Minjiao Zhang & Simge Küçükyavuz & Saumya Goel, 2014. "A Branch-and-Cut Method for Dynamic Decision Making Under Joint Chance Constraints," Management Science, INFORMS, vol. 60(5), pages 1317-1333, May.
    16. Hermann Held, 2019. "Cost Risk Analysis: Dynamically Consistent Decision-Making under Climate Targets," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 72(1), pages 247-261, January.
    17. Schweiger, Katharina & Sahamie, Ramin, 2013. "A hybrid Tabu Search approach for the design of a paper recycling network," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 50(C), pages 98-119.
    18. Shen, Feifei & Zhao, Liang & Wang, Meihong & Du, Wenli & Qian, Feng, 2022. "Data-driven adaptive robust optimization for energy systems in ethylene plant under demand uncertainty," Applied Energy, Elsevier, vol. 307(C).
    19. Wu, Desheng (Dash) & Lee, Chi-Guhn, 2010. "Stochastic DEA with ordinal data applied to a multi-attribute pricing problem," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1679-1688, December.
    20. Odetayo, Babatunde & MacCormack, John & Rosehart, William D. & Zareipour, Hamidreza, 2017. "A sequential planning approach for Distributed generation and natural gas networks," Energy, Elsevier, vol. 127(C), pages 428-437.

    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:wly:navres:v:67:y:2020:i:6:p:420-437. 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: https://doi.org/10.1002/(ISSN)1520-6750 .

    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.