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All issues Volume 355 (2026) EPJ Web Conf., 355 (2026) 01008 References
Open Access
Issue
EPJ Web Conf.
Volume 355, 2026
4th International Conference on Sustainable Technologies and Advances in Automation, Aerospace and Robotics (STAAAR 2025)
Article Number 01008
Number of page(s) 13
Section Robotics, Exoskeletons and AI Modeling
DOI https://doi.org/10.1051/epjconf/202635501008
Published online 03 March 2026
  1. J. K. Lenstra, A. R. Kan, P. Brucker, Complexity of machine scheduling problems., Annals of discrete mathematics, 1, 343–362, (1977) [Google Scholar]
  2. S. Ashour, S. R. Hiremath, A branch-and-bound approach to the job-shop scheduling problem, International Journal of Production Research, 11, 47–58, (1973), https://doi.org/10.1080/00207547308929945 [Google Scholar]
  3. S. Tian, C. Zhang, J. Fan, X. Li, L. Gao, A genetic algorithm with critical path-based variable neighborhood search for distributed assembly job shop scheduling problem., Swarm and Evolutionary Computation, 85, 101485, (2024), https://doi.org/10.1016/j.swevo.2024.101485 [Google Scholar]
  4. D. B. Fontes, M. M. Homayouni, S.M. J. F. Gonçalves, A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources., European Journal of Operational Research, 306, 1140–1157, (2023), https://doi.org/10.1016/j.ejor.2022.09.006 [Google Scholar]
  5. A. M. Ahmed, T. A. Rashid, S. Saeed, Cat Swarm Optimization Algorithm: A Survey and Performance Evaluation, Computational Intelligence and Neuroscience, 2020, 1–20, (2020), https://doi.org/10.1155/2020/4854895 [Google Scholar]
  6. K. R. Baker, D. Trietsch, Principles of sequencing and scheduling, (John Wiley & Sons, 2018) [Google Scholar]
  7. S. C. Chu, P. Tsai, J. S. Pan, Cat Swarm Optimization, PRICAI 2006: Trends in Artificial Intelligence, 4099, 854–858, (2006), https://doi.org/10.1007/978-3-540-36668-3_94 [Google Scholar]
  8. M. Orouskhani, Y. Orouskhani, M. Mansouri, M. Teshnehlab, A novel cat swarm optimization algorithm for unconstrained optimization problems, International Journal of Information Technology and Computer Science, 5, 32–41, (2013) [Google Scholar]
  9. D. Gabi, A. S. Ismail, A. Zainal, Z. Zakaria, A. Khasawneh, Hybrid cat swarm optimization and simulated annealing for dynamic task scheduling on cloud computing environment, Journal of Information and Communication Technology, 17, 435–467, (2018) [Google Scholar]
  10. A. O. Khedim, M. Souier, Z. Sari, Combinatorial artificial bee colony algorithm hybridised with a new release of iterated local search for job shop scheduling problem, International Journal of Operational Research, 44, 435, (2022) [Google Scholar]
  11. L. Songyang, Y. Haipeng, W. Miao, Cat swarm optimization algorithm based on the information interaction of subgroup and the top-N learning strategy, Journal of Intelligent Systems, 31, 489–500, (2022), https://doi.org/10.1515/jisys-2022-0018 [Google Scholar]
  12. A. Bouzidi, M. E. Riffi, Cat swarm optimization to solve job shop scheduling problem, 2014 Third IEEE International Colloquium in Information Science and Technology (CIST), 202–205, (2014) [Google Scholar]
  13. A. Bouzidi, M. E. Riffi, M. Barkatou, Cat swarm optimization for solving the open shop scheduling problem, Journal of Industrial Engineering International, 15, 367–378, (2019), https://doi.org/10.1007/s40092-018-0297-z [Google Scholar]
  14. S. Mahmud, R. K. Chakrabortty, A. Abbasi, M. J. Ryan, Switching strategy-based hybrid evolutionary algorithms for job shop scheduling problems, Journal of Intelligent Manufacturing, 33, 1939–1966, (2022), https://doi.org/10.1007/s10845-022-01940-1 [Google Scholar]
  15. A. Delgoshaei, M. K. Ariffin, Z. B. Leman, An Effective 4–Phased Framework for Scheduling Job-Shop Manufacturing Systems Using Weighted NSGA-II, Mathematics, 10, 4607, (2022) [Google Scholar]
  16. B. Khurshid, S. Maqsood, A hybrid evolution strategies-simulated annealing algorithm for job shop scheduling problems, Engineering Applications of Artificial Intelligence, 133, 108016, (2024) [Google Scholar]
  17. J. F. Gonçalves, J. J. Magalhães Mendes, M. G. de, Resende, A hybrid genetic algorithm for the job shop scheduling problem, European journal of operational research, 167, 77–95, (2005) [Google Scholar]
  18. J. E. Beasley, OR-Library: Distributing Test Problems by Electronic Mail, Journal of the Operational Research Society, 41, 1069–1072, (1990), https://doi.org/10.1057/jors.1990.166 [Google Scholar]
  19. H. Yu, Y. Gao, L. Wang, J. Meng, J, A hybrid particle swarm optimization algorithm enhanced with nonlinear inertial weight and Gaussian mutation for job shop scheduling problems, Mathematics, 8, 1355, (2020) [Google Scholar]

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