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Combination of mobile agentand evolutionary algorithm to optimizethe client transport services

Published online by Cambridge University Press:  21 February 2008

Hayfa Zgaya ,
Slim Hammadi  and
Khaled Ghédira
Hayfa Zgaya
Affiliation:
LAGIS UMR 8146 École Centrale de Lille, France; [email protected]; [email protected]
Slim Hammadi
Affiliation:
LAGIS UMR 8146 École Centrale de Lille, France; [email protected]; [email protected]
Khaled Ghédira
Affiliation:
SOIE, ISG-Tunis ISG, Tunis University, Tunisia; [email protected]
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Abstract

This paper presents a migration strategy for a set of mobile agents (MAs) in order to satisfy customers' requests in a transport network, through a multimodal information system. In this context, we propose an optimization solution which operates on two levels. The first one aims to constitute a set of MAs building their routes, called Workplans. At this level, Workplans must incorporate all nodes, representing information providers in the multimodal network, in order to explore it completely. Thanks to an evolutionary approach, the second level must optimize nodes selection in order to increase the number of satisfied users. The assignment of network nodes to the required services must be followed by a Workplan update procedure in order to deduce final routes paths. Finally, simulation results are mentioned to invoke the different steps of our adopted approach.

Keywords

Mobile agentsevolutionary algorithmsmultimodal information systemmultimodal transport network
Type
Research Article
Information
RAIRO - Operations Research , Volume 42 , Issue 1: Cooperative methods for multiobjective optimization , January 2008 , pp. 35 - 67
Copyright
© EDP Sciences, ROADEF, SMAI, 2008

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References

H. Zgaya, K. Ghédira and S. Hammadi, Proposition d'un système d'information multimodal à base d'agents mobiles destiné aux clients des réseaux de transport, in Proc. of the International Workshop of Méthodologies et Heuristiques pour l'Optimisation des Systèmes Industriels (MHOSI'05), Hammamet, Tunisia 24–26 April (2005).
S. Rouvrais, Utilisation d'agents mobiles pour la construction de services distribués. Ph.D. Thesis, University of Rennes, France (2002).
W. Theilmann and K. Rothermel, Efficient Dissemination of Mobile Agents, in Proc. of the 19th IEEE International Conference on Distributed Computing Systems Workshops (ICDCSW'99), edited by W. Sun, S. Chanson, D. Tygar and P. Dasgupta, Austin, TX, USA, 31 May–5 Juin (1999) 9–14.
A. Fugetta, G.P. Picco and G. Vigna, Understanding code mobility, IEEE Trans. Software Engineering 24(5) (1998) 342–361.
A. Carzaniga, G.P. Picco and G. Vigna, Designing distributed applications with mobile code paradigms, in Proc. of the 19th International Conference on Software Engineering (ICSE'97), Boston, Massachusetts, USA 17–23 May (1997). ACM Press (1997) 22–32.
D. Rus, R. Gray and D. Kotz, Autonomous and adaptive agents that gather information, in Proc. of the Thirteen National Conference on Artificial Intelligence Workshop on Intelligent Adaptive Agents (AAAI'96), Portland, Oregon, USA, 4–8 August (1996) 107–116.
J. Yang, V. Honavar, L. Miller and J. Wong, Intelligent Mobile Agents for information retrieval and knowledge discovery from distributed data and knowledge sources, in Proc. of the IEEE Information Technology Conference, Syracuse, NY USA, 1–3 September (1998) 99–102.
S. Green, L. Hurst, B. Nangle, P. Cunningham, F. Somers and R. Evans, Software agents: A review. Technical report, TCS-CS-1997-06, Trinity College Dublin, Ireland (1997).
D. Kotz and R.S. Gray, Mobile Agents and the Future of the Internet, Department of Computer Science, Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire 03755, ACM SIGOPS Operating Systems Review 33(3) (1999) 7–13.
G. Bernard, Technologie du code mobile: état de l'art et perspectives, in Proc. Of the Colloque Francophone sur l'Ingénierie des Protocoles (CFIP'99), Nancy, France April 26–29 (1999).
K. Moizumi, Mobile Agent Planning Problems. Ph.D. Thesis, Thayer School of Engineering, Dartmouth College, Hanover, NH 03755 USA (1998).
W. Caripe, G. Cybenko, K. Moizumi and R. Gray, Dartmouth Coll., Hanover, NH; Network awareness and mobile agent systems. IEEE Comm. Magazine, 36-7 (1998) 44–49.
K. Moizumi and G. Cybenko, The traveling agent problem. Mathematics of Control, Signals and Systems (1998).
H. Zgaya, S.Hammadi and K. Ghédira, Workplan Mobile Agent for the Transport Network Application, in Proc. of 17th IMACS World Congress Scientific Computation, Applied Mathematics and Simulation (IMACS'2005), Paris 11–15 July, (2005).
E. Horowitz and S.Sahni, Fundamentals of Computer Algorithms. Computer Science Press (1989).
J.W. Baek, J.H. Yeo, G.T. Kim and H.Y. Yeom, Cost effective mobile agent planning for distributed information retrieval, in Proc. of 21st International Conference on Distributed Computing Systems (ICDCS'01), Phoenix, Arizona USA, 16–19 April (2001) 65–72.
M. Garey and D. Johnson, Computers and Intractability: A Guide to the theory of NP-Completeness, W. H. Freeman and Co., USA (1979).
Z. Michalewicz, Genetic Algorithms + Data Structures = Evolution programs. Springer Verlag (1992).
H. Zgaya, S. Hammadi and K. Ghédira, Evolutionary method to optimize Workplan mobile agent for the transport network application, in Proc. of International Conference on Systems, Man and Cybernetics, (SMC'2005) 10–12 October Hawaii, USA, 2(2005) 1174–1179.
L. Davics, Handbook of genetic algorithm. New York: Van Nostrand Reinhold (1991).
M. Purvis, S. Crenefield, R. Ward, M. Nowostawski, D. Carter and G. Bush, A multi-agent system for the integration of distributed environmental information, Environmental Modelling & Software,Information Science Department, University of Otago, Dunedin, New Zealand, 18(6) (2003) 565–572.
E. Zitzler and L. Thiele, Multiobjective Optimization Using Evolutionary Algorithms: A Comparative Case Study, in Lect. Notes Comput. Sci. 1498 UK (1998) 292–301.
Java Agent DEvelopment framework. http://jade.tilab.com/doc
http://www.java.sun.com
http://www.fipa.org
D. Greenwood, JADE Web Service Integration Gateway (WSIG), WHITESTEIN Technologies. Jade Tutorial, in Fourth International Joint Conference on Autonomous Agents and Multi Agent Systems (AAMAS 2005), Utrecht University, the Netherlands, 25–29 July (2005).
K. Deb, S. Agrawal, A. Pratap and T. Meyarivan, A fast and elitist multi-objective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Computation, 6(2) (2002) 182–197.
G.P. Picco and M. Baldi, Evaluating the Tradeoffs of Mobile Code Design Paradigms in Network Management Applications, in Proc. of 20th IEEE International Conference on Software Engineering (ICSE'97), edited by R. Kemmerer and K. Futatsugi, Kyoto, Japan, April (1998) 146–155.
M. Ketel, N.S. Dogan and A. Homaifar, Distributed Sensor Networks based on Mobile Agents Paradigms, Dept. of Computer Science, North Carolina A&T State University, NC 27411, in Proc. of the Thirty-Seventh Southeastern Symposium on System Theory (SSST'05), Greensboro, USA, 20–22 March (2005) 411–414.
H. Zgaya and S. Hammadi, Assignment and Integration of Distributed Transport Services in Agent-Based Architecture, IEEE/WIC/ACM International Conference on Intelligent Agent Technology (IAT 2006 Main Conference Proceedings) (IAT'06), Hong Kong, China, 18–22 December (2006) 96–102.