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It is shown, through comparisons with Simulated Annealing (SA) algorithm, Simple Genetic Algorithm (SGA) and also optimal solutions obtained via mathematical model relaxed to fixed number of cells, that AGGA is capable of evolving optimal or near optimal solutions in a computationally efficient manner.
Stochastic methods, which are based on probabilistic algorithms, do not provide those guarantees, but are frequently capable of finding optimal or near-optimal solutions in affordable computation times.
Finally, the work describes an optimization method capable of producing optimal mesostructures.
This article presents an optimization scheme which is capable of designing optimal and robust metal forming processes efficiently.
The PSO [32] and GCGA [36] produce optimal results in some problems, but they are not capable of producing optimal solution in all runs of the algorithms for different test problems (at least up to a moderate size).
The results showed that 2 valve engine CC is not capable of creating optimal twin swirl.
In both cases, the proposed MIDO formulation was capable of finding optimal solutions.
The first approach concerns a variation-aware algorithm capable of extracting optimal design parameters to decrease variation and power.
The model is capable of identifying optimal investment strategies and build up of new capacities of an integrated gas supply system.
It is also capable of identifying optimal restoration scenarios from a range of scenarios generated by the newly developed decision-support system.
The aim of this approach is to obtain a control system capable of an optimal functioning in normal conditions and robust at perturbations.
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