Abstract
The increasing relevance of complex systems in dynamic environments has received special attention during the last decade from the researchers. Such systems need to satisfy products or clients desires, which, after accomplished might change, becoming a very dynamic situation. Currently, decentralized approaches could assist in the automation of dynamic scheduling, based on the distribution of control functions over a swarm network of decision-making entities. Distributed scheduling, in an automatic manner, can be answered by a service coordination architecture of the different schedule components. However, it is necessary to introduce the control layer in the solution, encapsulating an intelligent service that merge agents with optimization methods. Multi-agent systems (MAS) can be combined with several optimization methods to extract the best of the two worlds: the intelligent control, cooperation and autonomy provided by MAS solutions and the optimum offered by optimization methods. The proposal intends to test the intelligent management of the schedule composition quality, in two case studies namely, manufacturing and home health care.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Alves, F., Varela, M.L.R., Rocha, A.M.A.C., Pereira, A.I., Barbosa, J., Leitão, P.: Hybrid system for simultaneous job shop scheduling and layout optimization based on multi-agents and genetic algorithm. In: Madureira, A.M., Abraham, A., Gandhi, N., Varela, M.L. (eds.) HIS 2018. AISC, vol. 923, pp. 387–397. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-14347-3_38
Alves, F., Pereira, A.I., Barbosa, J., Leitão, P.: Scheduling of home health care services based on multi-agent systems. In: Bajo, J., et al. (eds.) PAAMS 2018. CCIS, vol. 887, pp. 12–23. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-94779-2_2
Çaliş, B., Bulkan, S.: A research survey: review of ai solution strategies of job shop scheduling problem. J. Intell. Manuf. 26(5), 961–973 (2015)
Gen, M., Lin, L.: Multiobjective evolutionary algorithm for manufacturing scheduling problems: state-of-the-art survey. J. Intell. Manuf. 25(5), 849–866 (2014). https://doi.org/10.1007/s10845-013-0804-4
Leitão, P., Barbosa, J.: Adaptive scheduling based on self-organized holonic swarm of schedulers. In: 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE), pp. 1706–1711, June 2014. https://doi.org/10.1109/ISIE.2014.6864872
Leitão, P., Restivo, F.: A holonic approach to dynamic manufacturing scheduling. Rob. Comput.-Integr. Manuf. 24(5), 625–634 (2008)
Ouelhadj, D., Petrovic, S.: A survey of dynamic scheduling in manufacturing systems. J. Sched. 12(4), 417 (2008)
Pinedo, M.L.: Scheduling: Theory, Algorithms, and Systems. Springer, Heidelberg (2016)
Trentesaux, D., Borangiu, T., Thomas, A.: Emerging ICT concepts for smart, safe and sustainable industrial systems. Comput. Ind. 81, 1–10 (2016). https://doi.org/10.1016/j.compind.2016.05.001. http://www.sciencedirect.com/science/article/pii/S0166361516300665. ISSN 0166-3615
Trentesaux, D., et al.: Benchmarking flexible job-shop scheduling and control systems. Control Eng. Pract. 21(9), 1204–1225 (2013)
Wooldridge, M.: An Introduction to MultiAgent Systems, 2nd edn. Wiley, Hoboken (2009)
Yang, Q., Yang, T., Li, W.: Smart Power Distribution Systems: Control, Communication, and Optimization. Elsevier Science, Amsterdam (2018)
Acknowledgments
This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Projects Scope: UID/CEC/00319/2019.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Alves, F., Rocha, A.M.A.C., Pereira, A.I., Leitao, P. (2019). Distributed Scheduling Based on Multi-agent Systems and Optimization Methods. In: De La Prieta, F., et al. Highlights of Practical Applications of Survivable Agents and Multi-Agent Systems. The PAAMS Collection. PAAMS 2019. Communications in Computer and Information Science, vol 1047. Springer, Cham. https://doi.org/10.1007/978-3-030-24299-2_27
Download citation
DOI: https://doi.org/10.1007/978-3-030-24299-2_27
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-24298-5
Online ISBN: 978-3-030-24299-2
eBook Packages: Computer ScienceComputer Science (R0)