EHBSAEdge Histogram Based Sampling Algorithm (genetics)
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Finally, for completeness, we compare the performance of traditional GA [41], HeSEA [42], LEM [30], SA [10], UMDA [43], EHBSA [44], ACS [45], and DPSO [46] by applying PR to all of them.
The results in Table 4 show that not only can the proposed algorithm reduce a great deal of the computation time of other efficient evolutionary algorithms such as UMDA and EHBSA, but it can also reduce the computation time of swarm intelligence algorithms such as ACS and DPSO while limiting the loss of the quality of the end result.
TABLE 4: Simulation results of UMDA, EHBSA, ACS, and DPSO.