Abstract
Dynamic enterprises process optimization (DEPO) is a multi-parametric and multi-objective system optimization problem. This paper proposes a simulation-based process model learning approach for dynamic enterprise process optimization. Some concepts such as Evolving_region, Evolving_Potential, Degenerate_region and Degenerate_limit are proposed to extend the concept of Tabu area. Tabu area extension and connection is successfully presented for realizing rapidly the domain reduction of a candidate set and speeding up global optimization. A distributed parallel optimization environment has been implemented using intelligent agents to validate the proposed approach.
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© 2006 Springer-Verlag Berlin Heidelberg
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Tan, W. (2006). A Simulation-Based Process Model Learning Approach for Dynamic Enterprise Process Optimization. In: Huang, DS., Li, K., Irwin, G.W. (eds) Computational Intelligence. ICIC 2006. Lecture Notes in Computer Science(), vol 4114. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-37275-2_53
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DOI: https://doi.org/10.1007/978-3-540-37275-2_53
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Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37274-5
Online ISBN: 978-3-540-37275-2
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