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We implemented an optimization routine that minimized the difference between the experiment and simulation lattice strains.
To this end, we implemented an optimization algorithm based on simulations applying finite element methods (FEMs), which maximizes the coil's sensitivity and thus signal-to-noise ratio (SNR) while incorporating boundary conditions such as the coil's electrical properties and a localized sensitivity needed for single-sided applications.
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In this work, the authors also implement an optimization tool which can specify the optimal power saving network topology.
This method allows finding an exact optimal solution to the IP problem by implementing an optimization software with no need to introduce advanced heuristic methods.
The main issue objective of this work is to implement an optimIzation strategy through a two-layer structure where the search for optimal operational variables is made through of the algorithms optimization - Successive quadratic programming - SQP.
This analytical approach is particularly useful for implementing an optimization design tool for GSHP systems.
The method implements an optimization procedure designed to identify the best hydrogen bonding network based on a generic scoring function.
The approach combines the software EnergyPlus and MATLAB® to implement an optimization genetic algorithm and a smart research strategy.
A skeleton in the mallba library implements an optimization method in one of the three families of generic optimization techniques offered: exact, heuristic and hybrid.
To test whether self-replication is maximized we implemented an evolutionary optimization algorithm that selects sequences for replication rate, without considering any interaction between genetically different individuals.
Zhang et al. (2016) implemented a systematic optimization approach to obtain the pareto-optimal values of cutting process parameters.
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