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Both algorithms have been optimized for modal analysis applications by a significant reduction of the computation time and memory requirements.

Both algorithms have been implemented on the Connection Machine CM2 massively parallel computer and execute at speeds suitable for interactive volume rendering applications.

Both algorithms have been studied with several decision making criteria: intercellular traffic, size of the machine cells, ratio of state space expansion, and so on.

Both algorithms have been applied to the same set of cell formation problems with alternate routings from literature and representative results are shown.

However, both algorithms have been applied to various science and engineering optimization problems, extensively, the algorithms suffer from premature convergence, unbalanced exploration-exploitation, and sometimes slow convergence speed.

The convergence characteristics of both algorithms have been shown in the graphs below (Fig. 2).

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Finally, a comparison of the performance of both algorithms has been carried out under different LTE and LTE-A scenarios, showing that the proposed eOLLA outperforms the traditional OLLA in all the cases.

The strategy where the final list of stringent CNVRs was found by both algorithms has been recommended previously in order to reduce the false discovery rate [ 25].

Both DE and TDE algorithms have been applied to seven dynamic optimization problems (five optimal control problems and two kinetic parameter estimation problems) taken from recent literature.

In addition to the theoretical foundations of both approaches, the algorithms have been implemented.

Both (EKF and UKF) navigation algorithms have been validated through experimental navigation data related to some sea tests performed in La Spezia Italyy) with one of Typhoon class vehicles during the NATO CommsNet13 experiment (held in September 2013) and through Ultra-Short BaseLine (USBL) fixes used as a reference (ground truth).

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