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Both of the algorithms are compared in terms of convergence rate and success of converging to an optimal solution.
In terms of convergence speed, the graph-based technique with the simultaneous scheduling converges faster than that with random scheduling, as in all the previous cases.
The four methods were compared in terms of convergence, accuracy and computation time.
Furthermore, an additional experimentation has been performed in terms of convergence.
A good performance in terms of convergence and computation times is evidenced.
The numerical technique was found to be very robust in terms of convergence and stability.
Results show that the proposed method outperforms the existing methods in terms of convergence performance and forecasting accuracy.
The performance of the FD-SCA in terms of convergence rate is further enhanced using normalization in frequency bins.
Simulation results show high performance for Modified Firefly Algorithm as compared to conventional Firefly Algorithm in terms of convergence rate.
The friendship centers significantly improved RIO in terms of convergence speed and stability with a minor 37.47% additional time cost.
Experimental studies demonstrate that the proposed HMOGWO outperforms other algorithms in terms of convergence, spread and coverage.
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