IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v248y2016i1p174-182.html
   My bibliography  Save this article

Project buffer sizing of a critical chain based on comprehensive resource tightness

Author

Listed:
  • Zhang, Junguang
  • Song, Xiwei
  • Díaz, Estrella

Abstract

A buffer sizing method based on comprehensive resource tightness is proposed in order to better reflect the relationships between activities and improve the accuracy of project buffer determination. Physical resource tightness is initially determined by setting a critical value of resource availability according to the law of diminishing marginal returns. The design structure matrix (DSM) is then adopted to analyze the information flow between activities and calculate the rework time resulting from the information interaction and the information resource tightness. Finally, the project buffer size is adjusted and determined by means of comprehensive resource tightness which consists of physical resource tightness and information resource tightness. The experimental results indicate that the proposed method considers the effect of comprehensive resource tightness on a project buffer, thus overcoming the deficiencies of traditional methods which consider only physical resource tightness and ignore information resource tightness. The size of the project buffer determined by the proposed method is more reasonable, thus signifying that it can doubly optimize project duration and cost.

Suggested Citation

  • Zhang, Junguang & Song, Xiwei & Díaz, Estrella, 2016. "Project buffer sizing of a critical chain based on comprehensive resource tightness," European Journal of Operational Research, Elsevier, vol. 248(1), pages 174-182.
    • Handle: RePEc:eee:ejores:v:248:y:2016:i:1:p:174-182
    DOI: 10.1016/j.ejor.2015.07.009
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221715006426
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ejor.2015.07.009?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. Golenko-Ginzburg, Dimitri & Gonik, Aharon, 1997. "Stochastic network project scheduling with non-consumable limited resources," International Journal of Production Economics, Elsevier, vol. 48(1), pages 29-37, January.
    2. Junguang Zhang & Xiwei Song & Hongyu Chen & Ruixia (Sandy) Shi, 2015. "Optimisation of critical chain sequencing based on activities’ information flow interactions," International Journal of Production Research, Taylor & Francis Journals, vol. 53(20), pages 6231-6241, October.
    3. Junguang Zhang & Ruixia Shi & Estrella Diaz, 2015. "Dynamic monitoring and control of software project effort based on an effort buffer," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(9), pages 1555-1565, September.
    4. Tukel, Oya I. & Rom, Walter O. & Eksioglu, Sandra Duni, 2006. "An investigation of buffer sizing techniques in critical chain scheduling," European Journal of Operational Research, Elsevier, vol. 172(2), pages 401-416, July.
    5. Burke, Edmund K. & Li, Jingpeng & Qu, Rong, 2010. "A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems," European Journal of Operational Research, Elsevier, vol. 203(2), pages 484-493, June.
    6. Eppinger, Steven D. & Browning, Tyson R., 2012. "Design Structure Matrix Methods and Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262017520, April.
    7. Lin, Jun & Qian, Yanjun & Cui, Wentian & Goh, Thong Ngee, 2015. "An effective approach for scheduling coupled activities in development projects," European Journal of Operational Research, Elsevier, vol. 243(1), pages 97-108.
    8. V González & L F Alarcón & T W Yiu, 2013. "Integrated methodology to design and manage work-in-process buffers in repetitive building projects," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(8), pages 1182-1193, August.
    9. Rabbani, M. & Fatemi Ghomi, S.M.T. & Jolai, F. & Lahiji, N.S., 2007. "A new heuristic for resource-constrained project scheduling in stochastic networks using critical chain concept," European Journal of Operational Research, Elsevier, vol. 176(2), pages 794-808, January.
    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. Mohammadreza Sharifi Ghazvini & Vahidreza Ghezavati & Sadigh Raissi & Ahmad Makui, 2017. "An Integrated Efficiency–Risk Approach in Sustainable Project Control," Sustainability, MDPI, vol. 9(9), pages 1-20, September.
    2. Milind Jagtap, 2020. "Predicting Penetration of the Project Buffer Time of Critical Chain Project Management (CCPM) Using a Linear Programming Approach," IIM Kozhikode Society & Management Review, , vol. 9(2), pages 143-151, July.
    3. Junguang Zhang & Xiwei Song & Estrella Díaz, 2017. "Critical chain project buffer sizing based on resource constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 55(3), pages 671-683, February.
    4. Asadabadi, Mehdi Rajabi & Zwikael, Ofer, 2021. "Integrating risk into estimations of project activities' time and cost: A stratified approach," European Journal of Operational Research, Elsevier, vol. 291(2), pages 482-490.
    5. Guofeng Ma & Shan Jiang & Tiancheng Zhu & Jianyao Jia, 2019. "A Novel Method of Developing Construction Projects Schedule under Rework Scenarios," Sustainability, MDPI, vol. 11(20), pages 1-25, October.
    6. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).
    7. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    8. She, Bingling & Chen, Bo & Hall, Nicholas G., 2021. "Buffer sizing in critical chain project management by network decomposition," Omega, Elsevier, vol. 102(C).
    9. Xuejun Hu & Jianjiang Wang & Kaijun Leng, 2019. "The Interaction Between Critical Chain Sequencing, Buffer Sizing, and Reactive Actions in a CC/BM Framework," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(03), pages 1-22, June.
    10. Xuejun Hu & Erik Demeulemeester & Nanfang Cui & Jianjiang Wang & Wendi Tian, 2017. "Improved critical chain buffer management framework considering resource costs and schedule stability," Flexible Services and Manufacturing Journal, Springer, vol. 29(2), pages 159-183, June.
    11. Junguang Zhang & Dan Wan, 2021. "Determination of early warning time window for bottleneck resource buffer," Annals of Operations Research, Springer, vol. 300(1), pages 289-305, May.
    12. Guofeng Ma & Jianyao Jia & Tiancheng Zhu & Shan Jiang, 2019. "A Critical Design Structure Method for Project Schedule Development under Rework Risks," Sustainability, MDPI, vol. 11(24), pages 1-20, December.

    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. Guofeng Ma & Jianyao Jia & Tiancheng Zhu & Shan Jiang, 2019. "A Critical Design Structure Method for Project Schedule Development under Rework Risks," Sustainability, MDPI, vol. 11(24), pages 1-20, December.
    2. Junguang Zhang & Xiwei Song & Hongyu Chen & Ruixia (Sandy) Shi, 2016. "Determination of critical chain project buffer based on information flow interactions," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(9), pages 1146-1157, September.
    3. Cui, Nanfang & Demeulemeester, Erik & Bie, Li, 2016. "Incorporation of activity sensitivity measures into buffer management to manage project schedule riskAuthor-Name: Hu, Xuejun," European Journal of Operational Research, Elsevier, vol. 249(2), pages 717-727.
    4. Xuejun Hu & Jianjiang Wang & Kaijun Leng, 2019. "The Interaction Between Critical Chain Sequencing, Buffer Sizing, and Reactive Actions in a CC/BM Framework," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(03), pages 1-22, June.
    5. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    6. Yan Zhao & Nanfang Cui & Wendi Tian, 2020. "A two-stage approach for the critical chain project rescheduling," Annals of Operations Research, Springer, vol. 285(1), pages 67-95, February.
    7. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).
    8. Junguang Zhang & Xiwei Song & Estrella Díaz, 2017. "Critical chain project buffer sizing based on resource constraints," International Journal of Production Research, Taylor & Francis Journals, vol. 55(3), pages 671-683, February.
    9. Guofeng Ma & Shan Jiang & Tiancheng Zhu & Jianyao Jia, 2019. "A Novel Method of Developing Construction Projects Schedule under Rework Scenarios," Sustainability, MDPI, vol. 11(20), pages 1-25, October.
    10. Bruni, M.E. & Di Puglia Pugliese, L. & Beraldi, P. & Guerriero, F., 2017. "An adjustable robust optimization model for the resource-constrained project scheduling problem with uncertain activity durations," Omega, Elsevier, vol. 71(C), pages 66-84.
    11. Uwe Beyer & Oliver Ullrich, 2022. "Organizational Complexity as a Contributing Factor to Underperformance," Businesses, MDPI, vol. 2(1), pages 1-15, March.
    12. Morgan Dwyer & Bruce Cameron & Zoe Szajnfarber, 2015. "A Framework for Studying Cost Growth on Complex Acquisition Programs," Systems Engineering, John Wiley & Sons, vol. 18(6), pages 568-583, November.
    13. Robert Schmidt & Kasper Sanchez Vibaek & Simon Austin, 2014. "Evaluating the adaptability of an industrialized building using dependency structure matrices," Construction Management and Economics, Taylor & Francis Journals, vol. 32(1-2), pages 160-182, February.
    14. Kaushik Sinha & Seok‐Youn Han & Eun Suk Suh, 2020. "Design structure matrix‐based modularization approach for complex systems with multiple design constraints," Systems Engineering, John Wiley & Sons, vol. 23(2), pages 211-220, March.
    15. Chen, Shih-Pin & Tsai, Ming-Jiun, 2011. "Time-cost trade-off analysis of project networks in fuzzy environments," European Journal of Operational Research, Elsevier, vol. 212(2), pages 386-397, July.
    16. Li, Haitao & Womer, Norman K., 2015. "Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 246(1), pages 20-33.
    17. Junguang Zhang & Dan Wan, 2021. "Determination of early warning time window for bottleneck resource buffer," Annals of Operations Research, Springer, vol. 300(1), pages 289-305, May.
    18. Juntao Zhang & Cecilia Haskins & Yiliu Liu & Mary Ann Lundteigen, 2018. "A systems engineering–based approach for framing reliability, availability, and maintainability: A case study for subsea design," Systems Engineering, John Wiley & Sons, vol. 21(6), pages 576-592, November.
    19. Nazarizadeh, Farzaneh & Alemtabriz, Akbar & Zandieh, Mostafa & Raad, Abbas, 2022. "An analytical model for reliability assessment of the rail system considering dependent failures (case study of Iranian railway)," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    20. Khraisha, Tamer, 2020. "Complex economic problems and fitness landscapes: Assessment and methodological perspectives," Structural Change and Economic Dynamics, Elsevier, vol. 52(C), pages 390-407.

    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:ejores:v:248:y:2016:i:1:p:174-182. 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/eor .

    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.