Perturbation Analysis of Steady-State Performance and Sensitivity-Based Optimization
We introduce the theories and methodologies that utilize the special features of discrete event dynamic systems (DEDSs) for perturbation analysis (PA) and optimization of steady-state performance. Such theories and methodologies usually take different perspectives from the traditional optimization approaches and therefore may lead to new insights and efficient algorithms. The topic discussed includes the gradient-based optimization for systems with continuous parameters and the direct-comparison-based optimization for systems with discrete policies, which is an alternative to dynamic programming and may apply when the latter fails. Furthermore, these new insights can also be applied to continuous-time and continuous-state dynamic systems, leading to a new paradigm of optimal control.
- Cao XR, Wan XW (2013) Analysis of non-linear behavior – a sensitivity-based approach. submittedGoogle Scholar