Abstract
This paper extends the deterministic energy optimization problem of flexible manufacturing systems (FMSs) recently presented in [1] with its robust counterpart, where both productive and idle powers are considered as random variables. Based on the weighted p-timed Petri net models of FMSs, the robust energy-optimal schedule is determined by searching the robust shortest path of reachability graph. We select the most suitable model of uncertainties for our robust shortest path problem and propose a novel robustness measure, called Renyi mean-entropy criterion, using Renyi quadratic entropy. Experiment results with energy data logged from an industrial stamping system verify the practicality of considered problem and the effectiveness of Renyi mean-entropy criterion for robustness measure in terms of computational complexity and deviation from optimality.
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