Abstract
In most cases, QoS-driven global optimization is a non-linear 0-1 programming. Genetic Algorithms are superior in non-linear 0-1 programming and multi-objective optimization. However, encoding methods that many Genetic Algorithms (GAs) adopts are too complex or simple to apply to services selection. A novel Tree-coding Gas (TGA) is presented for QoS-driven service selection in services composition. Tree-coding schema carries the messages of static model of service workflow, which qualifies TGA to encode and decode chromosomes automatically, and keeps the medial results for fitness computing. Tree-coding can also support the services composition flow re-planning at runtime effectively. The experiment results show that TGA run faster than one-dimensional Genetic Algorithms when the optimal result is the same, furthermore the algorithm with Tree-coding is effective for re-planning.
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© 2007 Springer-Verlag Berlin Heidelberg
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Gao, C., Cai, M., Chen, H. (2007). QoS-Driven Global Optimization of Services Selection Supporting Services Flow Re-planning. In: Chang, K.CC., et al. Advances in Web and Network Technologies, and Information Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4537. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72909-9_56
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DOI: https://doi.org/10.1007/978-3-540-72909-9_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72908-2
Online ISBN: 978-3-540-72909-9
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