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Resource Constrained Multi-Project Scheduling Problem with Resource Transfer Times

Author

Listed:
  • M. Suresh

    (L&T Institute of Project Management, Vadodara 390019, Gujarat, India)

  • Pankaj Dutta

    (Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, Mumbai 400076, India)

  • Karuna Jain

    (Shailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, Mumbai 400076, India)

Abstract

Scheduling multi-project is a complex decision making process. It involves the effective and timely allocation of resources to different projects. In the case of multi-project, resources are often transferred between the projects. It consumes both time and cost, when projects are situated in different geographic locations. As a result, the net present value (NPV) of multi-projects is significantly impacted by the resource transfer time. In this paper, a new genetic algorithm (GA) approach to the multi-project scheduling problem with resource transfer times is presented, where the NPV of all projects is maximized subject to renewable resource constraints. The paper also presents a heuristic approach using two phase priority rules for the same problem. We conduct a comprehensive analysis of 60 two-phase priority rules. The proposed GA approach is compared to the heuristic approach using the well-known priority rules. An extensive computational experiment is reported.

Suggested Citation

  • M. Suresh & Pankaj Dutta & Karuna Jain, 2015. "Resource Constrained Multi-Project Scheduling Problem with Resource Transfer Times," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 32(06), pages 1-30, December.
    • Handle: RePEc:wsi:apjorx:v:32:y:2015:i:06:n:s0217595915500487
    DOI: 10.1142/S0217595915500487
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    References listed on IDEAS

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    Cited by:

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    2. Junlong Peng & Mengyao Wang & Chao Peng & Ke Hu, 2022. "Research on extremely short construction period of engineering project based on labor balance under resource tolerance," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-18, March.
    3. Yanfen Zhang & Jinyao Ma & Haibin Zhang & Bin Yue, 2023. "Platform Resource Scheduling Method Based on Branch-and-Bound and Genetic Algorithm," Annals of Data Science, Springer, vol. 10(5), pages 1421-1445, October.
    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. Gómez Sánchez, Mariam & Lalla-Ruiz, Eduardo & Fernández Gil, Alejandro & Castro, Carlos & Voß, Stefan, 2023. "Resource-constrained multi-project scheduling problem: A survey," European Journal of Operational Research, Elsevier, vol. 309(3), pages 958-976.

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