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This is achieved by using robust optimization techniques to determine the optimal process settings of adjustable tools in the final roll forming stand.
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Using robust optimization approach (worst-case approach), we establish optimality theorems and duality theorems for ϵ-solutions for the fractional optimization problem.
The proposed tool uses robust optimization theory and is built to interact with any existing (non-robust) physical designer.
In addition, Jotshi et al. (2009) used robust optimization to schedule routes for vehicles after the disaster.
Based on previous works, those forces are computed by using a robust optimization scheme.
Then a subsequent controller design is formulated using robust stable constrained MPC optimization.
This work makes a step forward in the direction of conquering this challenge by taking into account channel uncertainty, and the robust counterpart of nominal problem, without channel uncertainty, is framed by using worst-case robust optimization theory.
In this section, we study the robust FSBB design via convex optimization by using the WCP optimization in the case of bounded microphone mismatches.
Worst-case approach [14] and Bayesian approach [15] are widely used in robust optimization problems.
The work in [33] used a robust optimization model for managing combined heat and power systems via linear decision rules.
In order to get reliable/robust optimal designs with respect to random parameter variations, by using stochastic optimization methods, the original random structural optimization problem must be replaced by an appropriate deterministic substitute problem.
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