Abstract
The manufacturing industry is an ever-changing environment with companies facing increasing external and internal challenges, such as economic crises, technological development and global competition. These challenges create the need for companies to constantly adapt as the environment around them changes. As such, companies are adopting a more proactive approach to manufacturing rather than the usual reactive process, by taking advantage of the ongoing move towards automation and system interconnectivity in the context of Industry 4.0.
In this work, we propose an agent-based architecture that presents a solution to project scheduling problems, with operation dependent setup time that is resource, material and human-resource constrained.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Lasi, H., Fettke, P., Kemper, H.G., Feld, T., Hoffmann, M.: Industry 4.0. Bus. Inf. Syst. Eng. 6(4), 239–242 (2014)
Rudtsch, V., Gausemeier, J., Gesing, J., Mittag, T., Peter, S.: Pattern-based business model development for cyber-physical production systems. Procedia CIRP 4, 313–319 (2014)
Kolberg, D., Zühlke, D.: Lean automation enabled by I4.0. IFAC-PapersOnLine 48(3), 1870–1875 (2015)
Krichen, S., Chaouachi, J.: The resource constrained project scheduling problem. Graph-Relat. Optim. Decis. Support Syst. 69–82 (2014). John Wiley & Sons. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118984260. ISBN 9781848217430
Ling, W., Huan-yu, Z., Xiao-long, Z.: Survey on Resource-Constrained Project Scheduling Under Uncertainty. Tsinghua Tongfang Knowledge Network Technology Co., Ltd, Beijing (2014)
Abdolshah, M.: A review of RCPSP approaches and solutions. Int. Trans. J. Eng. Manag. Appl. Sci. Technol. 5(4), 253–286 (2014)
Ren, H., Wang, Y.: A survey of multi-agent methods for solving resource constrained project scheduling problems. In: International Conference on Management and Service Science, Wuhan (2011)
Wooldridge, M., Jennings, N.R.: Agent theories, architectures, and languages: a survey. In: International Workshop on Agent Theories, Architectures, and Languages, pp. 1–39. Springer (1994)
French, S.: Sequencing and Scheduling: An Introduction to the Mathematics of the Job-shop. Wiley, Ottawa (1982)
Sadeh, N.: Look-Ahead Techniques for Micro-Opportunistic Job Shop Scheduling, Piitsburg (1991)
Pinedo, M.: Scheduling: Theory, Algorithms, and Systems. Springer (2012)
Myszkowski, P., Skowronski, M., Podlodowski, L.: Novel heuristic solutions for multi–skill RCPSP. In: Federated Conference on Computer Science and Information Systems (2013)
Reis, L.P.: Coordination in Multi Agent Systems: Applications in College Management and Robotic Football. Faculdade de Engenharia da Universidade do Porto, Porto (2003)
Dahlén, C., Elfsson, J.: An Analysis of the Current and Future ERP Market. Kungl Tekniska Hogskolan, Stockholm (1999)
Ahituv, N., Neumann, S., Zviran, M.: A system development methodology for ERP systems. J. Comput. Inf. Syst. 42, 56–67 (2002)
Durfee, E.H., Rosenschein, J.: Distributed problem solving and multi-agent systems: Comparisons and examples. AAAI Technical report, pp. 52–62 (1994)
Leitão, P.: Agent-based distributed manufacturing control: a state-of-the-art survey. Eng. Appl. Artif. Intell. 22, 979–991 (2009)
Lesser, V.R.: Cooperative multiagent systems: a personal view of the state of the art. IEEE Trans. Knowl. Data Eng. 11, 133–142 (1999)
Gu, P., Balasubramanian, S., Norrie, D.: Bidding based process planning and scheduling in MAS. Comput. Ind. Eng. 32, 477–496 (1997)
Andreev, M., Ivaschenko, A., Skobelev, P., Tsarev, A.: A multi-agent platform design for adaptive networks of intelligent production schedulers. IFAC Proc. Vol. 43, 78–83 (2010)
Shpilevoy, V., Shishov, A.: Multi-agent system “Smart Factory”. In: 11th IFAC Workshop on Intelligent Manufacturing Systems, S. Paulo (2013)
Martin, S., Ouelhadj, D., Deullens, P., Ozcan, E., Juan, A., Burke, E.: A multi agent based cooperative approach to scheduling and routing. Eur. J. Oper. Res. 254, 169–178 (2016)
Bellifemine, F., Caire, G.: JADE administrator’s guide. 08 April 2010. http://jade.tilab.com/doc/administratorsguide.pdf. Accessed 22 Feb 2018
IEEE FIPA: The Foundation for Intelligent Physical Agents. http://www.fipa.org. Accessed 20 Jan 2018
Vaucher, J., Ncho, A.: JADE tutorial and primer. April 2004. https://www.iro.umontreal.ca/~vaucher/Agents/Jade/Mobility.html. Accessed Feb 2018
Acknowledgments
This work was supported by NIS Project (ANI|P2020 21958) and has received funding from FEDER Funds through P2020 program and from National Funds through FCT – Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) under the project UID/EEA/00760/2013.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Mota, D. et al. (2019). A MAS Architecture for a Project Scheduling Problem with Operation Dependant Setup Times. In: Graña, M., et al. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18. SOCO’18-CISIS’18-ICEUTE’18 2018. Advances in Intelligent Systems and Computing, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-319-94120-2_17
Download citation
DOI: https://doi.org/10.1007/978-3-319-94120-2_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-94119-6
Online ISBN: 978-3-319-94120-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)