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However, this mapping process can critically affect the performance of a solution.
On the other hand, the increased complexity of mechatronic systems, resulting from the benificial interaction of components from various domains, requests the use of an appropriate design methodology in order to recognize the functionality and performance of a solution already at an early stage of the mechatronic design process and to shorten development time.
As the performance of a solution can be verified in polynomial time, MHMM is NP; and because MHMM is both NP-hard and NP, it is also NP-complete.
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The RMI mechanism makes it possible to have a straightforward implementation of a fine-grained parallel ant colony, but the performance of such a solution is poor.
The importance of device structure and active-layer processing when screening non-fullerene acceptors was demonstrated through the organic solar cell device performance optimization of a solution processable non-fullerene, all small-molecule bulk heterojunction (BHJ) blend.
Hence the global reward η is accordingly derived as the summation of all the local rewards: eta = sumlimits_{i} {eta_{i} } = sumlimits_{i} {frac{1}{{zeta_{i} kappa_{p}^{ast} + left| {e_{kappa,i} } right|}}} (16 This global reward η can be used to evaluate the performance of a candidate solution; generally, the larger the global reward, the better the current solution.
Hence, the relative performance of an optimal solution (MDP) against the solution for the LP relaxation is: frac{4gamma}{4gamma-gamma^{2}}. Figure 6 shows how performances in these two scenarios vary with γ.
It analyzes the performance of a navigation solution based on pseudorange and pseudorange rate measurements, generated through the processing of very weak signals of the Global Positioning System (GPS) L1/L5 and Galileo E1/E5 frequency bands.
Thus, a local reward function is designed to evaluate the performance of a candidate solution.
In the following section, we are going to study the system performance of a deployment solution using the CPLEX Optimizer to solve the problem in various system configurations.
Mathematical and computational thinking are integral to design by allowing engineers to run tests and mathematical models to assess the performance of a design solution before prototyping.
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