541
Views
8
CrossRef citations to date
0
Altmetric
Research Article

Dynamic scheduling of manufacturing systems: a product-driven approach using hyper-heuristics

ORCID Icon, & ORCID Icon
Pages 641-665 | Received 14 Nov 2020, Accepted 30 Apr 2021, Published online: 19 Jul 2021

References

  • Akkiraju, R., P. Keskinocak, S. Murthy, and F. Wu. 2001. “An Agent-based Approach for Scheduling Multiple Machines.” Applied Intelligence 14 (2): 135–144. doi:10.1023/A:1008363208898.
  • Anuradha, V.P. and Sumathi, D., 2015. “A survey on resource allocation strategies in cloud computing”. In: 2014 International Conference on Information Communication and Embedded Systems, ICICES 2014. Chennai, India: IEEE, 1–7.
  • Aydilek, H., and A. Allahverdi. 2012. “Heuristics for No-wait Flowshops with Makespan Subject to Mean Completion Time.” Applied Mathematics and Computation 219 (1): 351–359. doi:10.1016/j.amc.2012.06.024.
  • Blunck, H., D. Armbruster, and J. Bendul. 2018. “Setting Production Capacities for Production Agents Making Selfish Routing Decisions.” International Journal of Computer Integrated Manufacturing 31 (7): 664–674. doi:10.1080/0951192X.2017.1379097.
  • Borangiu, T., S. Raileanu, D. Trentesaux, T. Berger, and I. Iacob. 2014. “Distributed Manufacturing Control with Extended CNP Interaction of Intelligent Products.” Journal of Intelligent Manufacturing 25 (5): 1065–1075. doi:10.1007/s10845-013-0740-3.
  • Bouazza, W., D. Hamdadou, Y. Sallez, and D. Trentesaux. 2019. “Effective Dynamic Selection of Smart Products Scheduling Rules in FMS.” Manufacturing Letters 20: 45–48. doi:10.1016/j.mfglet.2019.05.004.
  • Bouazza, W., Sallez, Y., Aissani, N., and Beldjilali, B., 2015. A model for manufacturing scheduling optimization through learning intelligent products. In: Studies in Computational Intelligence. Cham, Switzerland: Springer International Publishing, 233–241.
  • Branke, J., S. Nguyen, C. W. Pickardt, and M. Zhang. 2016. “Automated Design of Production Scheduling Heuristics: A Review.” IEEE Transactions on Evolutionary Computation 20 (1): 110–124. doi:10.1109/TEVC.2015.2429314.
  • Burke, E. K., M. Gendreau, M. Hyde, G. Kendall, G. Ochoa, E. Özcan, and R. Qu. 2013. “Hyper-heuristics: A Survey of the State of the Art.” Journal of the Operational Research Society 64 (12): 1695–1724. doi:10.1057/jors.2013.71.
  • Burke, E.K., Hyde, M., Kendall, G., Ochoa, G., Özcan, E., and Woodward, J.R., 2010. A Classification of Hyper-heuristic Approaches. In: M. Gendreau and J.-Y. Potvin, eds. Handbook of metaheuristics. Boston, MA: Springer US, 449–468.
  • Burke, E.K., Hyde, M.R., Kendall, G., Ochoa, G., Özcan, E., and Woodward, J.R., 2019. A classification of hyper-heuristic approaches: Revisited. In: M.G. J.-Y. Potvin, ed. International Series in Operations Research and Management Science. New York, NY, USA: Springer, 453–477.
  • Çakar, T., and I. Cil. 2004. “Artificial Neural Networks for Design of Manufacturing Systems and Selection of Priority Rules.” International Journal of Computer Integrated Manufacturing 17 (3): 195–211. doi:10.1080/09511920310001607078.
  • Carlucci, D., P. Renna, S. Materi, and G. Schiuma. 2020. “Intelligent Decision-making Model Based on Minority Game for Resource Allocation in Cloud Manufacturing.” Management Decision 58 (11): 2305–2325. doi:10.1108/MD-09-2019-1303.
  • Chen, G., P. Wang, B. Feng, Y. Li, and D. Liu. 2020. “The Framework Design of Smart Factory in Discrete Manufacturing Industry Based on Cyber-physical System.” International Journal of Computer Integrated Manufacturing 33 (1): 79–101. doi:10.1080/0951192X.2019.1699254.
  • Chern, C. C., and Y. L. Liu. 2003. “Family-based Scheduling Rules of a Sequence-dependent Wafer Fabrication System.” IEEE Transactions on Semiconductor Manufacturing 16 (1): 15–24. doi:10.1109/TSM.2002.807742.
  • Chiang, T.-C., and L.-C. Fu. 2009. “Using a Family of Critical Ratio-based Approaches to Minimize the Number of Tardy Jobs in the Job Shop with Sequence Dependent Setup Times.” European Journal of Operational Research 196 (1): 78–92. doi:10.1016/j.ejor.2007.12.042.
  • Choi, B. K., and N. K. You. 2006. “Dispatching Rules for Dynamic Scheduling of One-of-a-kind Production.” International Journal of Computer Integrated Manufacturing 19 (4): 383–392. doi:10.1080/09511920500407541.
  • Corning, P. A. 2002. “The Re-emergence of “Emergence”: A Venerable Concept in Search of A Theory.” Complexity 7 (6): 18–30. doi:10.1002/cplx.10043.
  • Cowling, P., Kendall, G., and Soubeiga, E., 2001. “A hyperheuristic approach to scheduling a sales summit”. In: E. Burke and W. Erben, eds. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer Verlag, 176–190.
  • Fattahi, P., and A. Fallahi. 2010. “Dynamic Scheduling in Flexible Job Shop Systems by considering Simultaneously Efficiency and Stability.” CIRP Journal of Manufacturing Science and Technology 2 (2): 114– 123. doi:10.1016/j.cirpj.2009.10.001.
  • Framinan, J.M., Leisten, R., and Ruiz García, R., 2014. “Manufacturing Scheduling Systems”. 1st ed. Manufacturing Scheduling Systems: An Integrated View on Models, Methods and Tools. London: Springer London.
  • Gavett, J. 1965. “Three Heuristic Rules for Sequencing Jobs to a Single Production Facility.” Management Science 11 (8): 166–176.
  • Hawkins, D. M. 2004. “The Problem of Overfitting.” Journal of Chemical Information and Computer Sciences 44 (1): 1–12.
  • Henderson, D., Jacobson, S.H., and Johnson, A.W., 2006. “The Theory and Practice of Simulated Annealing”. In: F. Glover and G.A. Kochenberger, eds. Handbook of Metaheuristics. Boston: Kluwer Academic Publishers, 287–319.
  • Herrera, C., Berraf, S.B., and Thomas, A., 2012. “Viable System Model Approach for Holonic Product Driven Manufacturing Systems”. In: Service Orientation in Holonic and Multi-Agent Manufacturing Control. Berlin, Heidelberg: Springer, 169–181.
  • Hershauer, J. C., and R. J. Ebert. 1975. “Search and Simulation Selection of a Job-Shop Sequencing Rule.” Management Science 21 (7): 833–843.
  • Jorapur, V. S., V. S. Puranik, A. S. Deshpande, and M. Sharma. 2016. “A Promising Initial Population Based Genetic Algorithm for Job Shop Scheduling Problem.” Journal of Software Engineering and Applications 9 (5): 208–214.
  • Kalinowski, K., Krenczyk, D., and Grabowik, C., 2013. “Predictive - Reactive Strategy for Real Time Scheduling of Manufacturing Systems”. Applied Mechanics and Materials 307: 470–473.
  • Keddis, N., G. Kainz, and A. Zoitl. 2015. “Product-driven Generation of Action Sequences for Adaptable Manufacturing Systems.” IFAC-PapersOnLine 28 (3): 1502–1508.
  • Kim, D. Y., J. W. Park, S. Baek, K. B. Park, H. R. Kim, J. I. Park, H. S. Kim, B. B. Kim, H. Y. Oh, K. Namgung, and W. Baek. 2020. “A Modular Factory Testbed for the Rapid Reconfiguration of Manufacturing Systems.” Journal of Intelligent Manufacturing 31 (3): 661–680.
  • Lei, J., and Z. Y. Yang. 2013. “Disturbance Management Design for a Holonic Multiagent Manufacturing System by Using Hybrid Approach.” Applied Intelligence 38 (3): 267–278.
  • Leitão, P. 2009. “Agent-based Distributed Manufacturing Control: A State-of-the-art Survey.” Engineering Applications of Artificial Intelligence 22 (7): 979–991.
  • Liou, C. D., and Y. C. Hsieh. 2015. “A Hybrid Algorithm for the Multi-stage Flow Shop Group Scheduling with Sequence-dependent Setup and Transportation Times.” International Journal of Production Economics 170: 258–267.
  • Mascia, F., M. López-Ibáñez, J. Dubois-Lacoste, and T. Stützle. 2013. “From Grammars to Parameters: Automatic Iterated Greedy Design for the Permutation Flow-shop Problem with Weighted Tardiness.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7997 (LNCS): 321–334.
  • Morariu, O., Raileanu, S., Morariu, C., and Borangiu, T., 2014. “Multi-agent system for heterarchical product-driven manufacturing”. In: 2014 IEEE International Conference on Automation, Quality and Testing, Robotics. IEEE, 1–6.
  • Mousakhani, M. 2013. “Sequence-dependent Setup Time Flexible Job Shop Scheduling Problem to Minimise Total Tardiness.” International Journal of Production Research 51 (12): 3476–3487.
  • Nguyen, S., M. Zhang, M. Johnston, K. C. Tan, S. Member, M. Johnston, K. C. Tan, and S. Member. 2013. “A Computational Study of Representations in Genetic Programming to Evolve Dispatching Rules for the Job Shop Scheduling Problem.” IEEE Transactions on Evolutionary Computation 17 (5): 621–639.
  • Ochoa, G., Qu, R., and Burke, E.K., 2009. “Analyzing the landscape of a graph based hyper-heuristic for timetabling problems”. In: Proceedings of the 11th Annual conference on Genetic and evolutionary computation - GECCO ’09. New York, New York, USA: ACM Press, 341-348.
  • Ouelhadj, D., and S. Petrovic. 2009. “A Survey of Dynamic Scheduling in Manufacturing Systems.” Journal of Scheduling 12 (4): 417–431.
  • Pan, Q.-K., L. Gao, X.-Y. Li, and K.-Z. Gao. 2017. “Effective Metaheuristics for Scheduling a Hybrid Flowshop with Sequence-dependent Setup Times.” Applied Mathematics and Computation 303: 89–112.
  • Pannequin, R., G. Morel, and A. Thomas. 2009. “The Performance of Product-driven Manufacturing Control: An Emulation-based Benchmarking Study.” Computers in Industry 60 (3): 195–203.
  • Panwalkar, S. S., and W. Iskander. 1977. “A Survey of Scheduling Rules.” Operations Research 25 (1): 45–61.
  • Pérez-Rodríguez, R. and Hernández-Aguirre, A., 2018. “A hybrid estimation of distribution algorithm for flexible job-shop scheduling problems with process plan flexibility”. Applied Intelligence 48 (10): 3707–3734.
  • Pickardt, C. W., and J. Branke. 2012. “Setup-oriented Dispatching Rules - A Survey.” International Journal of Production Research 50 (20): 5823–5842.
  • Sallez, Y., T. Berger, D. Deneux, and D. Trentesaux. 2010. “The Lifecycle of Active and Intelligent Products: The Augmentation Concept.” International Journal of Computer Integrated Manufacturing 23 (10): 905–924.
  • Shahzad, A., and N. Mebarki. 2016. “Learning Dispatching Rules for Scheduling: A Synergistic View Comprising Decision Trees, Tabu Search and Simulation.” Computers 5 (1): 3.
  • Thomas, A., D. Trentesaux, and P. Valckenaers. 2012. “Intelligent Distributed Production Control.” Journal of Intelligent Manufacturing 23 (6): 2507–2512.
  • Trentesaux, D., C. Pach, A. Bekrar, Y. Sallez, T. Berger, T. Bonte, P. Leitão, and J. Barbosa. 2013. “Benchmarking Flexible Job-shop Scheduling and Control Systems.” Control Engineering Practice 21 (9): 1204–1225.
  • UPHF, 2020. “AIP-Priméca-Valenciennes [Online].” [Accessed 10 March 2021. Available from: http://www.uphf.fr/aipnpdc/sites/fr.aipnpdc/files/pdf/equipement-plateforme-valenciennes.pdf
  • Vázquez Rodríguez, J.A., Petrovic, S., and Salhi, A., 2007. “A Combined Meta-Heuristic with Hyper-Heuristic Approach to the Scheduling of the Hybrid Flow Shop with Sequence Dependent Setup Times and Uniform Machines”. In: Proceedings of the 3rd Multidisciplinary International Conference on Scheduling: Theory and Applications. Paris, France, 506–513.
  • Vieira, G. E., J. W. Herrmann, and E. Lin. 2003. “Rescheduling Manufacturing Systems: A Framework of Strategies, Policies, and Methods.” Journal of Scheduling 6 (1): 39–62.
  • Windt, K., T. Becker, O. Jeken, and A. Gelessus. 2010. “A Classification Pattern for Autonomous Control Methods in Logistics.” Logistics Research 2 (2): 109–120.
  • Zambrano Rey, G., T. Bonte, V. Prabhu, and D. Trentesaux. 2014. “Reducing Myopic Behavior in FMS Control: A Semi-heterarchical Simulation-optimization Approach.” Simulation Modelling Practice and Theory 46: 53–75.
  • Zhang, H., and U. Roy. 2019. “A Semantics-based Dispatching Rule Selection Approach for Job Shop Scheduling.” Journal of Intelligent Manufacturing 30 (7): 2759–2779.
  • Zhang, Y., J. Wang, S. Liu, and C. Qian. 2017. “Game TheoryBased Real-Time Shop Floor Scheduling Strategy and Method for Cloud Manufacturing.” International Journal of Intelligent Systems 32 (4): 437–463.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.