Abstract
Public Transportation Systems (PTSs) are always subjected to disturbances and need a real time monitoring and control to maintain its performance at acceptable levels. In PTS, several types of disturbances can affect buses such as accidents, delays and traffic jams that can also affect schedules so dramatically that these schedules could become useless. Consequently, it becomes a necessity to develop a Decision Support System (DSS) able to help human regulator in managing PTS efficiently, and to provide users with high quality services, in terms of punctuality, frequency and productivity. In this paper, a reactive and decentralized DSS is developed for the control of PTS based on the biological immune theory. This DSS is an artificial immune system, which presents many interesting capabilities, including identification, learning, memory and distributed parallel processing. Through experimental validation, we show that this exploratory approach seems to be promising.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Davidsson, P., Henesey, L., Ramstedt, L., Törnquist, J., Wernstedt, F.: An analysis of agent-based approaches to transport logistics. Transp. Res. Part C 13, 255–271 (2005)
Bouamrane, K., Tahon, C., Beldjilali, B.: Decision making system for regulation of a bimodal urban transportation system, associating classical and multi-agent approaches. INFORMATICA 16(3), 1–30 (2005)
Ezzedine, H., Trabelsi, A., Kolski, C.: Modeling of an interactive system with an agent-based architecture using Petri nets, application of the method to the supervision of a transport system. Math. Comput. Simul. 70, 358–376 (2006)
Balbo, F., Pinson, S.: Using intelligent agents for transportation regulation support system design. Transp. Res. Part C Emerg. Technol. 18(1), 140–156 (2010)
Rahal, D.D., Rahal, F., Chekroun, M.R.: Multi-agent system for modeling transport systems. European J. Sci. Res. 46, 80–89 (2010). ISSN 1450-216X
Dasgupta, D., Ji, Z., Gonzalez, F.: Artificial immune system (AIS) research in the last five years. In: The Congress on Evolutionary Computation (CEC 2003), vol. 1, pp. 123–130 (2003)
Darmoul, S., Elkosantini, S.: Artificial immunity to control disturbances in public transportation systems: concepts, mechanisms and a prototype implementation of a knowledge based decision support system. Int. J. Knowl.-Based Syst. 58, 58–76 (2014)
Hightower, R., Forrest, S., Perelson, A.: The Baldwin effect in the immune system: learning by somatic hypermutation. In: Mithchell, M., Belew, R. (eds.) Adaptive Individuals in Evolving Populations: Models and Algorithms. Addison-Wesley, Boston (1996)
Hofmeyr, S.A.: An interpretative introduction to the immune system. In: Cohen, I., Segel, L.A. (eds.) Design Principles for the Immune System and Other Distributed Autonomous Systems. Oxford University Press, Oxford (2000)
Perelson, A.S., Weisbuch, G.: Immunology for physicists. Rev. Mod. Phys. 69(4), 1219–1267 (1997)
Kim, J., Bentley, P.: The human immune system and network intrusion detection. In: 7th European Conference on Intelligent Techniques and Soft Computing, Aachen (1999)
Forrest, S., Perelson, A.S., Allen, L., Cherukuri, R.: Self-nonself discrimination in a computer. In: 1994 IEEE Computer Society Symposium on Research in Security and Privacy, 1994, Proceedings, pp. 202–212, 16–18 May 1994
Freitas, A.A., Timmis, J.: Revisiting the foundations of artificial immune systems: a problem-oriented perspective. In: Timmis, J., Bentley, P.J., Hart, E. (eds.) ICARIS 2003. LNCS, vol. 2787, pp. 229–241. Springer, Heidelberg (2003)
de Castro, L.N., Timmis, J.: Artificial Immune System: A New Computation Intelligence Approach. Springer, Berlin (2002)
Lau, H.Y.K., Wong, V.W.K.: An immunity-based distributed multiagent-control framework. IEEE Trans. Syst. Man Cybern. Part A Syst. Hum. 36(1), 91–108 (2006)
Taghezout, N., Ascar, B., Bessedik, I.: An agent based decision support system for spunlace nonwovens production management: case study of INOTIS Enterprise. In: Decision Support Systems, pp. 411–422 (2012)
Acknowledgments
This work was supported by NSTIP strategic program number (12-INF2820-02) in the Kingdom of Saudi Arabia. The authors would like to thank all personnel involved in this work.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Mnif, S., Elkosantini, S., Darmoul, S., Ben Said, L. (2016). An Immune Multi-agent Based Decision Support System for the Control of Public Transportation Systems. In: Bajo, J., et al. Highlights of Practical Applications of Scalable Multi-Agent Systems. The PAAMS Collection. PAAMS 2016. Communications in Computer and Information Science, vol 616. Springer, Cham. https://doi.org/10.1007/978-3-319-39387-2_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-39387-2_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-39386-5
Online ISBN: 978-3-319-39387-2
eBook Packages: Computer ScienceComputer Science (R0)