IDEAS home Printed from https://ideas.repec.org/a/spr/operea/v22y2022i1d10.1007_s12351-019-00544-7.html
   My bibliography  Save this article

Optimizing non-unit repetitive project resource and scheduling by evolutionary algorithms

Author

Listed:
  • Duc-Hoc Tran

    (Ho Chi Minh City University of Technology, Vietnam National University Ho Chi Minh, City (VNU-HCM))

  • Jui-Sheng Chou

    (National Taiwan University of Science and Technology)

  • Duc-Long Luong

    (Ho Chi Minh City University of Technology, Vietnam National University Ho Chi Minh, City (VNU-HCM))

Abstract

Repetitive project scheduling is a frequently encountered and challenging task in project planning. Researchers have developed numerous methods for the scheduling and planning of repetitive construction projects. However, almost all current repetitive scheduling methods are based on identical production units or they neglect the priorities of activities. This work presents a new hybrid evolutionary approach, called the fuzzy clustering artificial bee colony approach (FABC), to optimize resource assignment and scheduling for non-unit repetitive projects (NRP). In FABC, the fuzzy c-means clustering technique applies several multi-parent crossover operators to utilize population information efficiently and to improve convergence efficiency. The scheduling subsystem considers the following: (1) the logical relationships among activities throughout the project; (2) the assignment of multiple resources; and (3) the priorities of activities in groups to calculate project duration. Two numerical case studies are analyzed to demonstrate the use of the FABC-NRP model and its ability to optimize the scheduling of non-unit repetitive construction projects. Experimental results indicate that the proposed method yields the shortest project duration on average and deviation of optimal solution among benchmark algorithms considered herein and those considered previously. The outcomes will help project managers to prepare better schedules of repetitive projects.

Suggested Citation

  • Duc-Hoc Tran & Jui-Sheng Chou & Duc-Long Luong, 2022. "Optimizing non-unit repetitive project resource and scheduling by evolutionary algorithms," Operational Research, Springer, vol. 22(1), pages 77-103, March.
    • Handle: RePEc:spr:operea:v:22:y:2022:i:1:d:10.1007_s12351-019-00544-7
    DOI: 10.1007/s12351-019-00544-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12351-019-00544-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12351-019-00544-7?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. Wang, Yong-Jun & Zhang, Jiang-She & Zhang, Gai-Ying, 2007. "A dynamic clustering based differential evolution algorithm for global optimization," European Journal of Operational Research, Elsevier, vol. 183(1), pages 56-73, November.
    2. Wenping Zou & Yunlong Zhu & Hanning Chen & Xin Sui, 2010. "A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm," Discrete Dynamics in Nature and Society, Hindawi, vol. 2010, pages 1-16, November.
    3. Sachchida Nand Chaurasia & Shyam Sundar & Alok Singh, 2017. "Hybrid metaheuristic approaches for the single machine total stepwise tardiness problem with release dates," Operational Research, Springer, vol. 17(1), pages 275-295, April.
    4. Khaled El-Rayes & Osama Moselhi, 1998. "Resource-driven scheduling of repetitive activities," Construction Management and Economics, Taylor & Francis Journals, vol. 16(4), pages 433-446.
    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. M. Vanhoucke, 2006. "An efficient hybrid search algorithm for various optimization problems," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 06/365, Ghent University, Faculty of Economics and Business Administration.
    2. Mena, Rodrigo & Hennebel, Martin & Li, Yan-Fu & Zio, Enrico, 2014. "Self-adaptable hierarchical clustering analysis and differential evolution for optimal integration of renewable distributed generation," Applied Energy, Elsevier, vol. 133(C), pages 388-402.
    3. M. Vanhoucke, 2007. "An electromagnetic time/cost trade-off optimization in project scheduling," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 07/457, Ghent University, Faculty of Economics and Business Administration.
    4. Khalied Hesham Hyari & Khaled El-Rayes & Mohammad El-Mashaleh, 2009. "Automated trade-off between time and cost in planning repetitive construction projects," Construction Management and Economics, Taylor & Francis Journals, vol. 27(8), pages 749-761.
    5. M. Vanhoucke & K. Van Osselaer, 2004. "Work Continuity In A Real-Life Schedule: The Westerschelde Tunnel," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/271, Ghent University, Faculty of Economics and Business Administration.
    6. Ahmed Hassanein & Osama Moselhi, 2005. "Accelerating linear projects," Construction Management and Economics, Taylor & Francis Journals, vol. 23(4), pages 377-385.
    7. Byung-Cheon Choi & Myoung-Ju Park, 2021. "Single-machine scheduling with periodic due dates to minimize the total earliness and tardy penalty," Journal of Combinatorial Optimization, Springer, vol. 41(4), pages 781-793, May.
    8. Khalid Mekamcha & Mehdi Souier & Hakim Nadhir Bessenouci & Mohammed Bennekrouf, 2021. "Two metaheuristics approaches for solving the traveling salesman problem: an Algerian waste collection case," Operational Research, Springer, vol. 21(3), pages 1641-1661, September.
    9. Pierre Bonnal & Didier Gourc & Ari-pekka Hameri & Germain Lacoste, 2005. "A linear-discrete scheduling model for the resource-constrained project scheduling problem," Construction Management and Economics, Taylor & Francis Journals, vol. 23(8), pages 797-814.
    10. Khaled El-Rayes & Ramaneetharan Ramanathan & Osama Moselhi, 2002. "An object-oriented model for planning and control of housing construction," Construction Management and Economics, Taylor & Francis Journals, vol. 20(3), pages 201-210.

    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:spr:operea:v:22:y:2022:i:1:d:10.1007_s12351-019-00544-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.