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However, directional mutation operators for solving MaOPs are scarce.
The proposed algorithms introduce new crossover and mutation operators for the selection of the heuristics.
The design of mutation operators for AO programs must take these factors into account.
Initially the suitable mutation operators for both DEs used in DPD are investigated.
In our previous research, we designed a set of 26 mutation operators for AspectJ programs [12].
The crossover and mutation operators for the proposed algorithm are discussed in what follows.
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The double-bridge is a mutation operator for the Genetic Algorithm.
In this paper, we employ the mutation operator for decimal number in solution algorithm.
Figure 4 shows an example of the mutation operator for the four products, and PM is equal to 0.05.
Consequently, the powerful combination of MTLBO and BH and a novel self-adaptive wavelet mutation operator for the organization of the new robust algorithm are proposed in this work.
A preferred region-based adaptive Gaussian mutation operator for set-based evolution is expounded in "Adaptive Gaussian mutation guided by preferred regions".
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