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By Stewart Long, Roy Dowsing, Patrick Craven (auth.), Dr Ann Macintosh BSc, CEng, Mr Richard Ellis BSc, MSc, Dr Frans Coenen PhD (eds.)

ISBN-10: 1447106490

ISBN-13: 9781447106494

ISBN-10: 1852336730

ISBN-13: 9781852336738

The papers during this quantity are the referred purposes papers offered at ES 2002, the Twenty-second SGES overseas convention on wisdom established platforms and utilized man made Intelligence, to be held in Cambridge in the course of December 2002. the appliance flow is the most important annual show off in Europe of actual functions utilizing AI know-how. Papers provided during this quantity describe the applying of AI to deal with real-world difficulties, together with trade, production and defence and each significant AI procedure; and spotlight serious parts of luck (and failure) and current the advantages and classes of price to different builders. this is often the 10th quantity within the purposes and concepts in clever platforms sequence. The sequence serves as a key reference as to how AI know-how has enabled corporations to unravel complicated difficulties and achieve major company advantages. The Technical circulate papers are released as a better half quantity lower than the name study and improvement in clever structures XIX.

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Additional resources for Applications and Innovations in Intelligent Systems X: Proceedings of ES2002, the Twenty-second SGAI International Conference on Knowledge Based Systems and Applied Artificial Intelligence

Example text

We refer to M as the destination group and {s }uM the multicast group. In addition, T(s, M) may contain relay nodes (Steiner nodes), that is, the IMI 54 nodes in the multicast tree but not in the multicast group. Let Prt,s, d) be a unique path in the tree T from the source node s to a destination node dEM. The total cost of the tree T(s,M) is defined as the sum of the cost of all links in that tree and can be given by C(T(s,M)) = L C(e) ... r(I,M) The total delay of the path Prt,s, d) is simply the sum of the delay of all links along Prt,s, d): D(Pr(s,d))= LD(e) ..

Genetic Algorithms in Search, Optimisation and Machine Learning. Addisen-Wesley Publishing Company, Inc. M. D. Eynon. (1999). Triangulated Spatial Models and Neighbourhood Search: An Experimental Comparison with Quadtrees. The Visual Computer 15(5),235-248. Dejong, K. and Sarma, 1. (1993) Generation Gaps Revisited. Foundations of Genetic Algorithms -2-, D. Whitley, ed. Morgan-Kaufinann. Wall, M. GAlib - A C++ Library of Genetic Algorithm Components. edulga!. SESSION 2: ENGINEERING GA-Based Heuristic Algorithms for BandwidthDelay-Constrained Least-Cost Multicast Routing A.

Computers & Operations Research, 1986, 13: 533 - 549. R. (ed). Modem heuristic techniques for combinatorial problems. Blackwell Scientific Publications, Oxford, 1993. L. K. (eds). Local search in combinatorial optimisation. D. P. Optimisation by simulated annealing. Science, 1993,220: 671 - 680. Laporte, G. H. Routing problems: a bibliography. Annals of Operations Research, 1995,61:227 - 262. Le Pape, C. Implementation of resource constraints in ILOG SCHEDULE: a library for the development of constraint-based scheduling systems.

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Applications and Innovations in Intelligent Systems X: Proceedings of ES2002, the Twenty-second SGAI International Conference on Knowledge Based Systems and Applied Artificial Intelligence by Stewart Long, Roy Dowsing, Patrick Craven (auth.), Dr Ann Macintosh BSc, CEng, Mr Richard Ellis BSc, MSc, Dr Frans Coenen PhD (eds.)


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