A Simulation-Based Process Model Learning Approach for Dynamic Enterprise Process Optimization
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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