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A multi-agent system for decentralized multi-project scheduling with resource transfers

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  • Adhau, Sunil
  • Mittal, M.L.
  • Mittal, Abhinav

Abstract

The companies dealing with multiple projects are geographically distributed at different locations. These projects require local (always available to the concerned project) and global (shared among the projects) resources that are available in limited quantity. The global resources are generally required to be transferred physically among the projects, consuming significant amounts of both time and cost. The existing multi-agent systems for decentralized resource constrained multi-project scheduling problem (DRCMPSP) do not consider the resource transfer time and related cost for execution and control. We introduce DRCMPSP-RT that explicitly considers the transfer of shared global resources. This paper proposes a novel distributed multi-agent system using auctions based negotiation (DMAS/RIA) approach for the resource intervals and allocating multiple different types of shared resources amongst multiple competing projects.

Suggested Citation

  • Adhau, Sunil & Mittal, M.L. & Mittal, Abhinav, 2013. "A multi-agent system for decentralized multi-project scheduling with resource transfers," International Journal of Production Economics, Elsevier, vol. 146(2), pages 646-661.
    • Handle: RePEc:eee:proeco:v:146:y:2013:i:2:p:646-661
    DOI: 10.1016/j.ijpe.2013.08.013
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Ben Issa, Samer & Patterson, Raymond A. & Tu, Yiliu, 2021. "Solving resource-constrained multi-project environment under different activity assumptions," International Journal of Production Economics, Elsevier, vol. 232(C).
    2. Hartmann, Sönke & Briskorn, Dirk, 2022. "An updated survey of variants and extensions of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 297(1), pages 1-14.
    3. Li, Xingyu & Epureanu, Bogdan I., 2020. "An agent-based approach to optimizing modular vehicle fleet operation," International Journal of Production Economics, Elsevier, vol. 228(C).
    4. He, Yukang & Jia, Tao & Zheng, Weibo, 2023. "Tabu search for dedicated resource-constrained multiproject scheduling to minimise the maximal cash flow gap under uncertainty," European Journal of Operational Research, Elsevier, vol. 310(1), pages 34-52.
    5. Liu, Ying & Zhou, Jing & Lim, Andrew & Hu, Qian, 2023. "A tree search heuristic for the resource constrained project scheduling problem with transfer times," European Journal of Operational Research, Elsevier, vol. 304(3), pages 939-951.
    6. Yinfeng Xu & Rongteng Zhi & Feifeng Zheng & Ming Liu, 2022. "Competitive algorithm for scheduling of sharing machines with rental discount," Journal of Combinatorial Optimization, Springer, vol. 44(1), pages 414-434, August.
    7. Nadia Chaudry & Ingunn Vermedal & Kjetil Fagerholt & Maria Fleischer Fauske & Magnus Stålhane, 2020. "A decomposition solution approach to the troops-to-tasks assignment in military peacekeeping operations," The Journal of Defense Modeling and Simulation, , vol. 17(4), pages 357-371, October.
    8. Fink, Andreas & Gerhards, Patrick, 2021. "Negotiation mechanisms for the multi-agent multi-mode resource investment problem," European Journal of Operational Research, Elsevier, vol. 295(1), pages 261-274.
    9. 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.
    10. Wuliang Peng & Jiali lin & Jingwen Zhang & Liangwei Chen, 2022. "A bi-objective hierarchical program scheduling problem and its solution based on NSGA-III," Annals of Operations Research, Springer, vol. 308(1), pages 389-414, January.
    11. Bredael, Dries & Vanhoucke, Mario, 2023. "Multi-project scheduling: A benchmark analysis of metaheuristic algorithms on various optimisation criteria and due dates," European Journal of Operational Research, Elsevier, vol. 308(1), pages 54-75.
    12. Becker, Till & Illigen, Christoph & McKelvey, Bill & Hülsmann, Michael & Windt, Katja, 2016. "Using an agent-based neural-network computational model to improve product routing in a logistics facility," International Journal of Production Economics, Elsevier, vol. 174(C), pages 156-167.
    13. Rob Eynde & Mario Vanhoucke, 2020. "Resource-constrained multi-project scheduling: benchmark datasets and decoupled scheduling," Journal of Scheduling, Springer, vol. 23(3), pages 301-325, June.
    14. Mohammad Rostami & Morteza Bagherpour, 2020. "A lagrangian relaxation algorithm for facility location of resource-constrained decentralized multi-project scheduling problems," Operational Research, Springer, vol. 20(2), pages 857-897, June.

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