Exact(4)
The proposed scheduling algorithm HQCEA optimizes the network transmission period which increases the diversity of the solution space of functions and avoid trapping into local peak effectively.
A self-normalizing method is developed to eliminate the requirement of initial design process for normalization and improve diversity of the solution.
To avoid premature of PSO algorithm, an adaptive inertial weight based on sigmoid function is employed to improve the diversity of the solution space.
In the first phase, the Sigma method [21] is dedicated to accelerate the convergence and obtain an approximated Pareto front, then an ideal optimal particle method [22] is contributed to facilitate the diversity of the solution in the second phase.
Similar(56)
One is the balance factor that can maintain the diversity of the solutions.
The algorithm revealed a good convergence towards the Pareto front but the diversity of the solutions was a drawback.
Third, the quality and diversity of the solutions are improved when compared to the other popular algorithms.
During rule optimization, different parameters can be inserted to or removed from a rule, increasing the diversity of the solutions.
In the iterative process these techniques are applied to the feasible solutions in order to provide the probability of better solution and guarantee the diversity of the solutions.
This algorithm is based on echolocation features of microbats and frequency tuning technique to increase the diversity of the solutions in the population.
The multi-V-shaped transfer function helps the proposed algorithm to preserve the diversity of the solutions and thus refine the convergence rate of the proposed algorithm.
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