Abstract
Modern manufacturing enterprises are steadily moving towards open architectures wherein manufacturing activities are integrated with the activities of suppliers, customers, and partners within complex supply chains. Agent-based technology provides a natural way to design and implement such integration. We model the supply chain as a directed graph in which the vertices represent computers or individual agents and edges represent links. Thus the problem of enhancing the efficiency of mobile agents reduces to the problem of finding resource-constrained extremal paths in the graph. We study ε-approximation algorithms for solving the considered problems. We suggest a general three-stage technique, which follows and extends an earlier computational scheme in the literature for the constrained path problems (CPP). The new technique essentially improves on several earlier algorithms and also provides new aproach for contructing FPTAS for the CPP.
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References
Jennings, N.R., Wooldridge, M.J.: Applications of Intelligent Agents. In: Jennings, N.R., Wooldridge, M.J. (eds.) Agent Technology: Foundations, Applications, and Markets, pp. 3–28. Springer, Heidelberg (1998)
Shen, W., Norrie, D.H., Barthes, J.-P.: Multi-Agent Systems for Concurrent Intelligent Design and Manufacturing. Taylor and Francis, London (2001)
Shen, W., Xue, D., Norrie, D.H.: An Agent-Based Manufacturing Enterprise Infrastructure for Distributed Integrated Intelligent Manufacturing Systems. In: Proceedings of the Third International Conference on the Practical Application of Intelligent Agents and Multi-Agents, London, UK, March 23-25, pp. 1–16 (1997)
Shen, W., Hao, Q., Yoon, H.J., Norrie, D.H.: Applications of Agent-Based Systems in Intelligent Manufacturing: An Updated Review. Advanced Engineering Informatics 20, 415–431 (2006)
White, J.E.: Telescript Technology: The Foundation for the Electronic Marketplace, White Paper, General Magic, Inc. USA (1994)
Tsichritzis, D.: Objectworld, Office Automation. Springer, Heidelberg (1985)
Papaioannou, T.: Using Mobile Agents to Improve the Alignment between Manufacturing and its IT Support Systems. Robotics and Autonomous Systems (1999)
Peng, Y., Finin, T., Labrou, Y., Chu, B., Long, J., Tolone, X., Boughannam, A.: A Multi-Agent System for Enterprise Integration. In: Proc. of PAAM 1998, London, UK, pp. 155–169 (1998)
Shen, W., Maturana, F., Norrie, D.H.: MetaMorph II: An Agent-Based Architecture for Distributed Intelligent Design and Manufacturing. Journal of Intelligent Manufacturing 11(3), 237–251 (2000)
Shen, W.: Distributed Manufacturing Scheduling Using Intelligent Agents. IEEE Intelligent Systems 17(1), 88–94 (2002)
Camponogaro, E., Shima, R.B.: Mobile Agent Routing with Time Constraints: A Resource Constrained Longest-Path Approach. Journal of Universal Computer Science 16(3), 372–401 (2010)
Elalouf, A., Levner, E.: General Techniques for Accelerating FPTAS for the Routing and Knapsack Problems, Abstract Book. In: Annual Meeting 2011 of Operations Research Society of Israel (ORSIS 2011), Akko, Israel, May 29-30, p. 14 (2011)
Brewington, B., Gray, R., Moizumi, K., Kotz, D., Cybenko, G., Rus, D.: Mobile Agents in Distributed Information Retrieval. In: Klusch, M. (ed.) Intelligent Information Agents, pp. 355–395. Springer, Heidelberg (1999)
Hassin, R.: Approximation Schemes for the Restricted Shortest Path Problem. Mathematics of Operations Research 17(1), 36–42 (1992)
Goel, A., Ramakrishnan, K.G., Kataria, D., Logothetis, D.: Efficient Computation of Delay-sensitive Routes from One Source to All Destinations. In: IEEE Infocom 2001, pp. 854–858. IEEE Press, Los Alamitos (2001)
Xue, G., Sen, A., Zhang, W., Tang, J., Thulasiraman, K.: Finding a Path Subject to Many Additive QoS Constraints. IEEE Transactions on Networking 15, 201–211 (2007)
Gens, G.V., Levner, E.V.: Fast Approximation Algorithms for Job Sequencing with Deadlines. Discrete Applied Mathematics 3, 313–318 (1981)
Papaioannou, T., Edwards, J.: Mobile Agent Technology Enabling the Virtual Enterprise: A Pattern for Database Query. In: Working Notes of the ABM Workshop, Minneapolis, MN, pp. 106–116 (1998)
Sadeh, N., Hildum, D.W., Kjenstad, D.: Agent-Based e-Supply Chain Decision Support. Journal of Organizational Computing and Electronic Commerce 33(3-4), 225–241 (2003)
Pan, J.Y.C., Tenenbaum, M.J.: An Intelligent Agent Framework for Enterprise Integration. IEEE Transactions on Systems, Man, and Cybernetics 21(6), 1391–1408 (1991)
Rech, L., Oliveira, R.S., Montez, C.B.: Dynamic Determination of the Itinerary of Mobile Agents with Timing Constraints. In: Proc. IEEE/WIC/ACM International Conference on Intelligent Agent Technology, Compiegne, France, pp. 45–50 (2005)
Gens, G.V., Levner, E.V.: Fast Approximation Algorithms for Knapsack Type Problems. LNCIS, vol. 23. Springer, Berlin (1980)
Cormen, T.H., Leiserson, C.E., Rivest, R.L., Stein, C.: Introduction to Algorithms. MIT Press, Cambridge (2001)
Lorenz, D.H., Raz, D.: A Simple Efficient Approximation Scheme for the Restricted Shortest Path problem. Operations Research Letters 28(5), 213–219 (2001)
Sahni, S.: Algorithms for Scheduling Independent Tasks. Journal of the ACM 23(1), 116–127 (1976)
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Elalouf, A., Levner, E., Cheng, T.C.E. (2011). Efficient Routing of Mobile Agents for Agent-Based Integrated Enterprise Management: A General Acceleration Technique. In: Barjis, J., Eldabi, T., Gupta, A. (eds) Enterprise and Organizational Modeling and Simulation. EOMAS 2011. Lecture Notes in Business Information Processing, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24175-8_1
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DOI: https://doi.org/10.1007/978-3-642-24175-8_1
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