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The present approach provides significant advantage of randomization over other existing optimization techniques for obtaining the optimal solution.
By using gradient-descent based optimization techniques, we solve the existing optimization problem and obtain the corresponding optimality system in a systematic manner.
However, due to the shortcomings of existing optimization theories and the complexity of rock masses, optimizing the smooth blasting parameters in arbitrary geological conditions with specified control indices is challenging.
However, the existing optimization methods for SO2 conversion rate can hardly achieve the optimal effect, because the parameters change and the working conditions fluctuate during the production process.
The existing optimization methods or formulations in the literature do not seem to be completely satisfactory.
Second, the optimization problem obtained has to be solvable in real time with existing optimization algorithms.
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Such observations put a question mark on suitability of the existing optimization-based routing solutions in WMNs.
Simulated examples show that the two-stage IMC has superior performance when compared to other existing optimization-based antiwindup methods.
This paper extends existing optimization-based methods that jointly identify the process and friction model parameters, so that a nonlinear process model structure is considered.
A free-matrix-based inequality method is developed by introducing a set of slack variables, which can be optimized via existing convex optimization algorithms.
The use of an MILP model guarantees convergence to optimality by using existing classical optimization methods.
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