IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i12p9252-d1166305.html
   My bibliography  Save this article

Optimal Scheduling of Rainwater Collection Vehicles: Mixed Integer Programming and Genetic Algorithms

Author

Listed:
  • Mohammed Alnahhal

    (Mechanical and Industrial Engineering Department, American University of Ras Al Khaimah, Ras Al Khaimah P.O. Box 10021, United Arab Emirates)

  • Nikola Gjeldum

    (Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB), University of Split, 21000 Split, Croatia)

  • Bashir Salah

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

Abstract

Due to climate change, some areas in the world witnessed higher levels of heavy rain than the capacity of the wastewater system of the streets. Therefore, water tankers are used for the dewatering process to take the extra rainwater from the streets to keep a smooth flow of vehicles and to use the water in agriculture and industry. Water is taken to a water treatment plant. Performing the dewatering process as fast as possible, especially in crowded streets, was ignored by researchers. In this study, at first, the problem was solved using two mixed integer programming (MIP) models. A new variant of identical parallel machine scheduling with job splitting is proposed for the first time, where one or at most two tankers can work at the same flood location at the same time. This is performed in the second model. However, the first model considers dividing the dewatering processes into two phases, where the first one, which is more urgent, is to reduce the amount of floodwater. The second one is for dewatering the rest of the water. Then two genetic algorithms (GAs) were used to solve faster the two MIP models, which are NP-hard problems. At first, the MIP and GA models were applied to small-sized problems. Then GA was used for large practical data sets. Results showed that for small problems, MIP and GA gave optimal solutions in a reasonable number of iterations, while for larger problems, good solutions were obtained in a reasonable number of iterations.

Suggested Citation

  • Mohammed Alnahhal & Nikola Gjeldum & Bashir Salah, 2023. "Optimal Scheduling of Rainwater Collection Vehicles: Mixed Integer Programming and Genetic Algorithms," Sustainability, MDPI, vol. 15(12), pages 1-18, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:12:p:9252-:d:1166305
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/12/9252/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/12/9252/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fleszar, Krzysztof & Hindi, Khalil S., 2018. "Algorithms for the unrelated parallel machine scheduling problem with a resource constraint," European Journal of Operational Research, Elsevier, vol. 271(3), pages 839-848.
    2. Jun-Ho Lee & Hoon Jang, 2019. "Uniform Parallel Machine Scheduling with Dedicated Machines, Job Splitting and Setup Resources," Sustainability, MDPI, vol. 11(24), pages 1-23, December.
    3. Lee, Young Hoon & Pinedo, Michael, 1997. "Scheduling jobs on parallel machines with sequence-dependent setup times," European Journal of Operational Research, Elsevier, vol. 100(3), pages 464-474, August.
    4. Khaled Alkhaledi & Allison Arnold & Kenneth Means & In-Ju Kim & Salaheddine Bendak, 2020. "A Novel Multicriteria Decision Making Model for Sustainable Stormwater Management," Sustainability, MDPI, vol. 12(22), pages 1-19, November.
    5. Burak Cankaya & Ezra Wari & Berna Eren Tokgoz, 2019. "Practical approaches to chemical tanker scheduling in ports: a case study on the Port of Houston," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(4), pages 559-575, December.
    6. Mauro Dell'Amico & Manuel Iori & Silvano Martello & Michele Monaci, 2008. "Heuristic and Exact Algorithms for the Identical Parallel Machine Scheduling Problem," INFORMS Journal on Computing, INFORMS, vol. 20(3), pages 333-344, August.
    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. Eirini Aivazidou & Naoum Tsolakis, 2023. "Water Management and Environmental Engineering: Current Practices and Opportunities," Sustainability, MDPI, vol. 15(15), pages 1-3, August.

    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. Donghun Lee & Hyeongwon Kang & Dongjin Lee & Jeonwoo Lee & Kwanho Kim, 2023. "Deep Reinforcement Learning-Based Scheduler on Parallel Dedicated Machine Scheduling Problem towards Minimizing Total Tardiness," Sustainability, MDPI, vol. 15(4), pages 1-14, February.
    2. Dung-Ying Lin & Tzu-Yun Huang, 2021. "A Hybrid Metaheuristic for the Unrelated Parallel Machine Scheduling Problem," Mathematics, MDPI, vol. 9(7), pages 1-20, April.
    3. Alidaee, Bahram & Kochenberger, Gary A. & Amini, Mohammad M., 2001. "Greedy solutions of selection and ordering problems," European Journal of Operational Research, Elsevier, vol. 134(1), pages 203-215, October.
    4. Jun-Ho Lee & Hyun-Jung Kim, 2021. "A heuristic algorithm for identical parallel machine scheduling: splitting jobs, sequence-dependent setup times, and limited setup operators," Flexible Services and Manufacturing Journal, Springer, vol. 33(4), pages 992-1026, December.
    5. Geurtsen, M. & Didden, Jeroen B.H.C. & Adan, J. & Atan, Z. & Adan, I., 2023. "Production, maintenance and resource scheduling: A review," European Journal of Operational Research, Elsevier, vol. 305(2), pages 501-529.
    6. Yepes-Borrero, Juan C. & Perea, Federico & Ruiz, Rubén & Villa, Fulgencia, 2021. "Bi-objective parallel machine scheduling with additional resources during setups," European Journal of Operational Research, Elsevier, vol. 292(2), pages 443-455.
    7. Mujawar, Sachin & Huang, Simin & Nagi, Rakesh, 2012. "Scheduling to minimize stringer utilization for continuous annealing operations," Omega, Elsevier, vol. 40(4), pages 437-444.
    8. Muter, İbrahim, 2020. "Exact algorithms to minimize makespan on single and parallel batch processing machines," European Journal of Operational Research, Elsevier, vol. 285(2), pages 470-483.
    9. Allahverdi, Ali & Gupta, Jatinder N. D. & Aldowaisan, Tariq, 1999. "A review of scheduling research involving setup considerations," Omega, Elsevier, vol. 27(2), pages 219-239, April.
    10. Rujapa Nanthapodej & Cheng-Hsiang Liu & Krisanarach Nitisiri & Sirorat Pattanapairoj, 2021. "Hybrid Differential Evolution Algorithm and Adaptive Large Neighborhood Search to Solve Parallel Machine Scheduling to Minimize Energy Consumption in Consideration of Machine-Load Balance Problems," Sustainability, MDPI, vol. 13(10), pages 1-25, May.
    11. Tao Dai & Xiangqi Fan, 2021. "Multi-Stove Scheduling for Sustainable On-Demand Food Delivery," Sustainability, MDPI, vol. 13(23), pages 1-13, November.
    12. Pohl, Maximilian & Kolisch, Rainer & Schiffer, Maximilian, 2021. "Runway scheduling during winter operations," Omega, Elsevier, vol. 102(C).
    13. Xi, Yue & Jang, Jaejin, 2012. "Scheduling jobs on identical parallel machines with unequal future ready time and sequence dependent setup: An experimental study," International Journal of Production Economics, Elsevier, vol. 137(1), pages 1-10.
    14. Y H Kang & S S Kim & H J Shin, 2010. "A dispatching algorithm for parallel machines with rework processes," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 144-155, January.
    15. J. E. Beasley & M. Krishnamoorthy & Y. M. Sharaiha & D. Abramson, 2000. "Scheduling Aircraft Landings—The Static Case," Transportation Science, INFORMS, vol. 34(2), pages 180-197, May.
    16. Ferretti, Ivan & Zanoni, Simone & Zavanella, Lucio, 2006. "Production-inventory scheduling using Ant System metaheuristic," International Journal of Production Economics, Elsevier, vol. 104(2), pages 317-326, December.
    17. Shim, Sang-Oh & Kim, Yeong-Dae, 2007. "Scheduling on parallel identical machines to minimize total tardiness," European Journal of Operational Research, Elsevier, vol. 177(1), pages 135-146, February.
    18. Kim, Kap Hwan & Park, Young-Man, 2004. "A crane scheduling method for port container terminals," European Journal of Operational Research, Elsevier, vol. 156(3), pages 752-768, August.
    19. Michele Ciavotta & Carlo Meloni & Marco Pranzo, 2016. "Speeding up a Rollout algorithm for complex parallel machine scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4993-5009, August.
    20. Sesh Murthy & Rama Akkiraju & Richard Goodwin & Pinar Keskinocak & John Rachlin & Frederick Wu & James Yeh & Robert Fuhrer & Santhosh Kumaran & Alok Aggarwal & Martin Sturzenbecker & Ranga Jayaraman &, 1999. "Cooperative Multiobjective Decision Support for the Paper Industry," Interfaces, INFORMS, vol. 29(5), pages 5-30, October.

    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:gam:jsusta:v:15:y:2023:i:12:p:9252-:d:1166305. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.