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Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming

Citations

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Cited by:

  1. Zhu, Xia & Ruiz, Rubén & Li, Shiyu & Li, Xiaoping, 2017. "An effective heuristic for project scheduling with resource availability cost," European Journal of Operational Research, Elsevier, vol. 257(3), pages 746-762.
  2. Rostami, Salim & Creemers, Stefan & Leus, Roel, 2024. "Maximizing the net present value of a project under uncertainty: Activity delays and dynamic policies," European Journal of Operational Research, Elsevier, vol. 317(1), pages 16-24.
  3. Luca Bertazzi & Riccardo Mogre & Nikolaos Trichakis, 2024. "Dynamic Project Expediting: A Stochastic Shortest-Path Approach," Management Science, INFORMS, vol. 70(6), pages 3748-3768, June.
  4. Deng, Qichen & Santos, Bruno F., 2022. "Lookahead approximate dynamic programming for stochastic aircraft maintenance check scheduling optimization," European Journal of Operational Research, Elsevier, vol. 299(3), pages 814-833.
  5. Brčić, Mario & Katić, Marija & Hlupić, Nikica, 2019. "Planning horizons based proactive rescheduling for stochastic resource-constrained project scheduling problems," European Journal of Operational Research, Elsevier, vol. 273(1), pages 58-66.
  6. Salim Rostami & Stefan Creemers & Roel Leus, 2018. "New strategies for stochastic resource-constrained project scheduling," Journal of Scheduling, Springer, vol. 21(3), pages 349-365, June.
  7. Goli, Alireza, 2024. "Efficient optimization of robust project scheduling for industry 4.0: A hybrid approach based on machine learning and meta-heuristic algorithms," International Journal of Production Economics, Elsevier, vol. 278(C).
  8. Balouka, Noemie & Cohen, Izack, 2021. "A robust optimization approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 291(2), pages 457-470.
  9. Chunlai Yu & Xiaoming Wang & Qingxin Chen, 2025. "Efficient Rollout Algorithms for Resource-Constrained Project Scheduling with a Flexible Project Structure and Uncertain Activity Durations," Mathematics, MDPI, vol. 13(9), pages 1-25, April.
  10. Seddik, Yasmina & Hanzálek, Zdenek, 2017. "Match-up scheduling of mixed-criticality jobs: Maximizing the probability of jobs execution," European Journal of Operational Research, Elsevier, vol. 262(1), pages 46-59.
  11. Yu Wu & Bo Zeng & Ming Jian, 2025. "ADP- and rollout-based dynamic vehicle routing for pick-up service via budgeting capacity," Flexible Services and Manufacturing Journal, Springer, vol. 37(2), pages 513-557, June.
  12. Ripon K. Chakrabortty & Ruhul A. Sarker & Daryl L. Essam, 2020. "Single mode resource constrained project scheduling with unreliable resources," Operational Research, Springer, vol. 20(3), pages 1369-1403, September.
  13. Marlin W. Ulmer & Justin C. Goodson & Dirk C. Mattfeld & Marco Hennig, 2019. "Offline–Online Approximate Dynamic Programming for Dynamic Vehicle Routing with Stochastic Requests," Service Science, INFORMS, vol. 53(1), pages 185-202, February.
  14. Sha, Yue & Zhang, Junlong & Cao, Hui, 2021. "Multistage stochastic programming approach for joint optimization of job scheduling and material ordering under endogenous uncertainties," European Journal of Operational Research, Elsevier, vol. 290(3), pages 886-900.
  15. Morteza Davari & Erik Demeulemeester, 2019. "Important classes of reactions for the proactive and reactive resource-constrained project scheduling problem," Annals of Operations Research, Springer, vol. 274(1), pages 187-210, March.
  16. Silva, Thiago A.O. & de Souza, Mauricio C., 2020. "Surgical scheduling under uncertainty by approximate dynamic programming," Omega, Elsevier, vol. 95(C).
  17. Thul, Lawrence & Powell, Warren, 2023. "Stochastic optimization for vaccine and testing kit allocation for the COVID-19 pandemic," European Journal of Operational Research, Elsevier, vol. 304(1), pages 325-338.
  18. Ursavas, Evrim, 2017. "A benders decomposition approach for solving the offshore wind farm installation planning at the North Sea," European Journal of Operational Research, Elsevier, vol. 258(2), pages 703-714.
  19. Fei, Xin & Branke, Jürgen & Gülpınar, Nalân, 2025. "Dynamic pharmaceutical product portfolio management with flexible resource profiles," European Journal of Operational Research, Elsevier, vol. 324(1), pages 308-323.
  20. Xichao Su & Wei Han & Yu Wu & Yong Zhang & Jie Liu, 2018. "A Proactive Robust Scheduling Method for Aircraft Carrier Flight Deck Operations with Stochastic Durations," Complexity, Hindawi, vol. 2018, pages 1-38, November.
  21. Zhalechian, M. & Tavakkoli-Moghaddam, R. & Zahiri, B. & Mohammadi, M., 2016. "Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 89(C), pages 182-214.
  22. Xue Luo & Li Li & Lei Zhao & Jianfeng Lin, 2022. "Dynamic Intra-Cell Repositioning in Free-Floating Bike-Sharing Systems Using Approximate Dynamic Programming," Transportation Science, INFORMS, vol. 56(4), pages 799-826, July.
  23. Satic, U. & Jacko, P. & Kirkbride, C., 2024. "A simulation-based approximate dynamic programming approach to dynamic and stochastic resource-constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 315(2), pages 454-469.
  24. Marlin W. Ulmer, 2020. "Horizontal combinations of online and offline approximate dynamic programming for stochastic dynamic vehicle routing," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 279-308, March.
  25. Hongli Yu & Yuelin Gao & Le Wang & Jiangtao Meng, 2020. "A Hybrid Particle Swarm Optimization Algorithm Enhanced with Nonlinear Inertial Weight and Gaussian Mutation for Job Shop Scheduling Problems," Mathematics, MDPI, vol. 8(8), pages 1-17, August.
  26. Ulmer, Marlin W. & Thomas, Barrett W., 2020. "Meso-parametric value function approximation for dynamic customer acceptances in delivery routing," European Journal of Operational Research, Elsevier, vol. 285(1), pages 183-195.
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