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A survey of hybrid metaheuristics for the resource-constrained project scheduling problem

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  • Pellerin, Robert
  • Perrier, Nathalie
  • Berthaut, François

Abstract

The Resource-Constrained Project Scheduling Problem (RCPSP) is a general problem in scheduling that has a wide variety of applications in manufacturing, production planning, project management, and various other areas. The RCPSP has been studied since the 1960s and is an NP-hard problem. As being an NP-hard problem, solution methods are primarily heuristics. Over the last two decades, the increasing interest in operations research for metaheuristics has resulted in a general tendency of moving from pure metaheuristic methods for solving the RCPSP to hybrid methods that rely on different metaheuristic strategies. The purpose of this paper is to survey these hybrid approaches. For the primary hybrid metaheuristics that have been proposed to solve the RCPSP over the last two decades, a description of the basic principles of the hybrid metaheuristics is given, followed by a comparison of the results of the different hybrids on the well-known PSPLIB data instances. The distinguishing features of the best hybrids are also discussed.

Suggested Citation

  • Pellerin, Robert & Perrier, Nathalie & Berthaut, François, 2020. "A survey of hybrid metaheuristics for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 280(2), pages 395-416.
    • Handle: RePEc:eee:ejores:v:280:y:2020:i:2:p:395-416
    DOI: 10.1016/j.ejor.2019.01.063
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    Cited by:

    1. Changjiu Li & Yong Zhang & Xichao Su & Xinwei Wang, 2022. "An Improved Optimization Algorithm for Aeronautical Maintenance and Repair Task Scheduling Problem," Mathematics, MDPI, vol. 10(20), pages 1-25, October.
    2. Xabier A. Martin & Rosa Herrero & Angel A. Juan & Javier Panadero, 2024. "An Agile Adaptive Biased-Randomized Discrete-Event Heuristic for the Resource-Constrained Project Scheduling Problem," Mathematics, MDPI, vol. 12(12), pages 1-21, June.
    3. Pejman Peykani & Jafar Gheidar-Kheljani & Sheida Shahabadi & Seyyed Hassan Ghodsypour & Mojtaba Nouri, 2023. "A two-phase resource-constrained project scheduling approach for design and development of complex product systems," Operational Research, Springer, vol. 23(1), pages 1-25, March.
    4. 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.
    5. Alimoradi, Mahmoud & Azgomi, Hossein & Asghari, Ali, 2022. "Trees Social Relations Optimization Algorithm: A new Swarm-Based metaheuristic technique to solve continuous and discrete optimization problems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 194(C), pages 629-664.
    6. Shahsavar, Aria & Sadeghi, J. Kiarash & Shockley, Jeff & Ojha, Divesh, 2021. "On the relationship between lean scheduling and economic performance in shipbuilding: A proposed model and comparative evaluation," International Journal of Production Economics, Elsevier, vol. 239(C).
    7. 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.
    8. Dhahri, Akrem & Gharbi, Ali & Ouhimmou, Mustapha, 2022. "Integrated production-delivery control policy for an unreliable manufacturing system and multiple retailers," International Journal of Production Economics, Elsevier, vol. 245(C).
    9. David Roch-Dupré & Carlos Camacho-Gómez & Asunción P. Cucala & Silvia Jiménez-Fernández & Álvaro López-López & Antonio Portilla-Figueras & Ramón R. Pecharromán & Antonio Fernández-Cardador & Sancho Sa, 2021. "Optimal Location and Sizing of Energy Storage Systems in DC-Electrified Railway Lines Using a Coral Reefs Optimization Algorithm with Substrate Layers," Energies, MDPI, vol. 14(16), pages 1-19, August.
    10. Alfredo S. Ramos & Pablo A. Miranda-Gonzalez & Samuel Nucamendi-Guillén & Elias Olivares-Benitez, 2023. "A Formulation for the Stochastic Multi-Mode Resource-Constrained Project Scheduling Problem Solved with a Multi-Start Iterated Local Search Metaheuristic," Mathematics, MDPI, vol. 11(2), pages 1-25, January.
    11. 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.
    12. Linh Nguyen Mai Vu & Hieu Chi Tran & Anh Thi Tram Nguyen, 2024. "A study on constructing an efficient examination scheduling system," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ENGINEERING AND TECHNOLOGY, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 14(1), pages 52-64.
    13. Neufeld, Janis S. & Schulz, Sven & Buscher, Udo, 2023. "A systematic review of multi-objective hybrid flow shop scheduling," European Journal of Operational Research, Elsevier, vol. 309(1), pages 1-23.
    14. Camur, Mustafa C. & Sharkey, Thomas C. & Vogiatzis, Chrysafis, 2023. "The stochastic pseudo-star degree centrality problem," European Journal of Operational Research, Elsevier, vol. 308(2), pages 525-539.
    15. 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.
    16. Swan, Jerry & Adriaensen, Steven & Brownlee, Alexander E.I. & Hammond, Kevin & Johnson, Colin G. & Kheiri, Ahmed & Krawiec, Faustyna & Merelo, J.J. & Minku, Leandro L. & Özcan, Ender & Pappa, Gisele L, 2022. "Metaheuristics “In the Large”," European Journal of Operational Research, Elsevier, vol. 297(2), pages 393-406.
    17. Florian Mischek & Nysret Musliu, 2021. "A local search framework for industrial test laboratory scheduling," Annals of Operations Research, Springer, vol. 302(2), pages 533-562, July.
    18. Fernando Acebes & David Poza & Jose M Gonzalez-Varona & Javier Pajares & Adolfo Lopez-Paredes, 2024. "On the project risk baseline: integrating aleatory uncertainty into project scheduling," Papers 2406.00077, arXiv.org.
    19. Neumann, Anas & Hajji, Adnene & Rekik, Monia & Pellerin, Robert, 2022. "A model for advanced planning systems dedicated to the Engineer-To-Order context," International Journal of Production Economics, Elsevier, vol. 252(C).
    20. Florian Mischek & Nysret Musliu & Andrea Schaerf, 2023. "Local search approaches for the test laboratory scheduling problem with variable task grouping," Journal of Scheduling, Springer, vol. 26(5), pages 457-477, October.
    21. Nataliia Dotsenko & Igor Chumachenko & Andrii Galkin & Heorhii Kuchuk & Dmytro Chumachenko, 2023. "Modeling the Transformation of Configuration Management Processes in a Multi-Project Environment," Sustainability, MDPI, vol. 15(19), pages 1-13, September.
    22. Alireza Tavakolian & Alireza Rezaee & Farshid Hajati & Shahadat Uddin, 2023. "Hospital Readmission and Length-of-Stay Prediction Using an Optimized Hybrid Deep Model," Future Internet, MDPI, vol. 15(9), pages 1-21, September.
    23. Neumann, Anas & Hajji, Adnene & Rekik, Monia & Pellerin, Robert, 2024. "Integrated planning and scheduling of engineer-to-order projects using a Lamarckian Layered Genetic Algorithm," International Journal of Production Economics, Elsevier, vol. 267(C).
    24. Zhao, Mingxuan & Zhou, Jian & Wang, Ke & Pantelous, Athanasios A., 2023. "Project scheduling problem with fuzzy activity durations: A novel operational law based solution framework," European Journal of Operational Research, Elsevier, vol. 306(2), pages 519-534.

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